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Recos : a request-commitment support model Lu, Feng 1992-12-18

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RECOS: A REQUEST-COMMITMENTSUPPORT MODELByFENG LUB. Eng., The University of Iron and Steel Technology, Beijing, 1982A THESIS SUBMHmD IN THE PARTIAL FULFILMENT OFTHE REQUIREMENTS FOR THE DEGREE OFMASTER OF SCIENCEinTHE FACULTY OF GRADUATE STUDIESMANAGEMENT INFORMATION SYSTEMSWe accept this thesis as conformingto the required standardThe UNIVERSITY OF BRITISH COLUMBIAAugust 1992® Feng Lu, 1992In presenting this thesis in partial fulfilment of the requirements for an advanceddegree at the University of British Columbia, I agree that the Library shall make itfreely available for reference and study. I further agree that permission for extensivecopying of this thesis for scholarly purposes may be granted by the head of mydepartment or by his or her representatives. It is understood that copying orpublication of this thesis for financial gain shall not be allowed without my writtenpermission.VDepartment of iY )_ç.The University of British ColumbiaVancouver, CanadaDatetn’) i,?,PoDE-6 (2/88)AbstractOrganizational work often requires cooperation among workers to achieve task completion.One type of cooperation can be described by the pair <request, commitment>, where a“commitment” is defined as an agreement with the requester to carry out the requested action.When a worker receives a request, he must decide what to do with it. In general, manyrequests demand the responder’s future action, and require substantial resources to complete.For these types of requests, the worker goes through a reasoning process to decide whetherhe should commit to doing the requested work. The research question of this thesis is: canwe build a computerized system to support an individual’s reasoning process in establishinga commitment? In this thesis, a computer-based quest-mmitment Support (RECOS)model is presented in attempting to answer this question.The RECOS model is primarily based on the commitment theory in sociology, the social rulesystem theory, the contract theory, and artificial intelligence techniques. It proposes that themost relevant factors determining an agent’s commitment are: 1) resource gains/losses, 2) theagent’s competence for fulfilling the requested action, 3) requester, the relationship betweenthe requester and responder, and the related others’ expectations of the agent’s decision aboutthe request, 4) organizational regulations, and 5) the agent’s previous commitments.A computer-based system built on RECOS would assist a user to select the relevant factorsand to evaluate these factors, as well as to integrate the evaluation results, in order to makea better justified and consistent commitment. Specifically, it would be able to provide a userwith the following support which, we believe, is not typical of traditional decision supportsystems:•Alerting the user when he makes a commitment that conflicts with priorcommitments• Suggesting those individuals that the user can ask to work jointly on therequest• Considering sentimental attributes•Conducting simple, single-issue negotiation with the requester or othercollaborators• Automatically processing standard requests• Providing limited learning capability (i.e., through case base) in handlingnon-standard requestsA user evaluation of the model has been conducted and the feedback appears promising. Aprototype based on the model has been developed using Turbo-Prolog to demonstrate how asystem built on the model operates.11Table of ContentsAbstract 11Table of ContentsList of Tables.List of Figures111viviiAcknowledgement viiiIntroduction1.1 Background and Motivation1.2 The Goal of the Thesis1.3 The Outline of the Thesis1123II. Related Work 42.1 Past Computer-Supported Collaborative Work Based on Commitment 42.1.1 An Early Work 42.1.2 A Commitment Maintenance Model2.1.3 A Domain Dependent System2.1.4 Formal Reasoning on Commitment2.1.5 An Organizational Model Based on Commitment2.2 Other Related Work2.2.1 Competence Assessment2.2.2 Negotiation2.2.3 Belief2.3 Summaryifi. Commitment3.1 The Commitment Concept3.2 Commitment from the Sociological Perspective3.3 A Formulation of Commitment3.4 Commitment vs. Decision3.5 Commitment vs. Contract3.6 SummaryIV. RECOS: A Request-Commitment Support Model.4.1 Boundaries and Assumptions of the Model . .4.1.1 Boundary4.1.2 Assumptions1717171845566777810101112131415111343435394242424344484849525253575757634.2 Factors Related to Commitments 184.2.1 Resources 194.2.2 Requester, Inter-agent Relationship, and Others’ Expectations . . . 204.2.3 Regulations 204.2.4 Commitment Connections 214.2.5 Direct Gains/Losses 224.2.6 Beliefs 234.2.7 Summary 234.3 The RECOS Model 244.3.1 Overview of the Model 244.3.2 Knowledge Bases 264.3.3 Components of the Reasoning Process 274.3.4 Summary 294.4 Discussion 314.4.1 A General and Flexible Reasoning Framework 314.4.2 Adaptability 314.4.3 Relationship of RECOS and Scheduling Systems 314.4.4 Relationship of RECOS and Traditional Decision SupportSystems 32V. RECOS Model and Reasoned Action Theory5.1. A Reasoned Action Theory5.2. An Innovation Adoption Model Based on Reasoned Action Theory. .5.3. Relation of the RECOS Model and Reasoned Action TheoryVI. Applications of the RECOS Model6.1 A Sample Application Using the Model6.1.1 A Brief Description of the Example6.1.2 Knowledge in the System and the Reasoning Process6.1.3 A Sample Dialogue6.1.4 Discussion6.2 User Evaluation6.2.1 The Design of the Prototype for the Evaluation6.2.2 The Subjects and the Scenarios6.2.3 The Conduct of the Evaluation6.2.4 DiscussionVII. Prototyping7.1 Objective of the Prototyping7.2 The Prototype Structure and Features7.3 DiscussionivVIII. Conclusion.658.1 Contributions 658.2 Limitations and Research Directions 66References 68Appendix 72VList of TablesTable 1. Summary of the Information Flow in the RECOS Model 30Table 2. Comparisons of RECOS Model, A Reasoned Action Model, andan Innovation Adoption Model 41viList of FiguresFigure 1. The Logical Structure and Reasoning Process of the RECOS Model 25Figure 2. A Reasoned Action Model 36Figure 3. An Innovation Adoption Model 38Figure 4. The main menu of the evaluation prototype 50Figure 5. The others’ expectations of the evaluation prototype 50Figure 6. The competence assessment of the evaluation prototype . . 51Figure 7. The tangible resource requirement of the evaluation prototype 51Figure 8. RECOS Prototype Structure 58Figure 9. A preprocessing menu when the system has no experience 60Figure 10. A Preprocessing menu when the system has experience . 61Figure 11. Acquiring information on inter-agent relationship 61Figure 12. A factor evaluation result report 62Figure 13. A menu after showing the evaluation result 63viiAcknowledgementI am deeply grateful to Professor Carson Woo, my supervisor, for his long-termcontinuedencouragement, great patience, sharp-minded advice and criticism, personal care andsupportthroughout my graduate studies, and particularly, during my thesis work period.I cannotimagine how this thesis could have been accomplished without his brilliant guidance.I am also grateful to Dr. Yair Wand and Dr. Chino Rao, my thesis committeemembers, forproviding me with insightful comments, and for helping me toclarify some key concepts.Many other people have contributed to the accomplishment of this thesis. Inparticular, I owea special thanks to Carla Weaver for her timely editorial assistance duringthe preparation of thefinal version of this thesis, to Dr. Ken Maccrimmon for directing me to contracttheory, to Dr.Al Dexter and Dr. Izak Benbasat for their feedback on an early version of my thesisproposal,to Man-Kit Chang and Thomas Hofbauer, my fellow MIS graduates at the Universityof BritishColumbia, for their constant encouragement and support of my work, to Jie Ding,Andy Fok,Kai-Hin Lim, Lia-huat Lim, Alaric Lui, John Lui, Becky Luk, Jiye Mao, and ClarenceMartensfor their trial of my prototype and providing me with useful feedback.The author is a member of the Institute for Robotics and Intelligent System(IRIS) and wishesto acknowledge the support of the Networks of Centres of ExcellenceProgram of theGovernment of Canada, the Natural Science and Engineering ResearchCouncil, and theParticipation of PRECARN Associates Inc.Finally, I am most grateful for the greatest patience and understanding of my wife, Xin.Withouther strong support, this thesis would have been impossible. I am especiallyindebted to my son,Hao, as I was not able to spend much time with him during this project.yinChapter 1IntroductionOrganizational work often requires cooperation among workers to achieve task completion. Onetype of cooperation can be described by the pair <request, commitment> [F1GrHW 88], wherea “commitment” is defined as an agreement with the requester to carry out the requested action.In other words, when a worker initiates a request for a commitment from his peer, cooperationis reached if the peer replies with a commitment and actually fulfils the commitment inaccordance with the agreed upon terms. Initially, when the peer receives a request, he mustdecide what to do with it. In general, many requests demand the receiver’s future action andrequire substantial resources to complete. For these types of requests, the worker goes througha reasoning process to decide whether he should commit to doing the requested work. Ourresearch question is: can we build a computerized system to support an individual’s reasoningprocess in establishing a commitment? In this thesis, we present a computer-basedquest-mmitment support (RECOS) model to attempt to answer this question. In theremainder of this chapter, we will discuss the background and motivation of this research, setup the thesis objectives, and present the outline of the thesis.1.1 Background and MotivationSince the early 1980s, information systems researchers have been modelling organizationalactivities based on the “commitment” concept. A number of models for supporting agentcommitments have been proposed [Fikes 81, F1GrHW 88, Koo 88, HaJaRo 90, Bond901.Someof them focus on modelling organizational activities from a collective perspective (e.g., [Fikes81, Bond 90]); and some of them focus on inter-agent communication and commitmentmaintenance (e.g., [F1GrHW 88, Koo 88, and HaJaRo 90]). Although they are important forunderstanding and supporting organizational activities, none of these models has fullyincorporated the reasoning process employed by a person to commit to something (e.g., how1a commitment is reached). Consequently, there is no sufficient support provided for such aprocess. We agree with the observation by Bhandaru and Croft (90, p.340) that “there is apatent lack of theories of individual activity in cooperative environment.” We believe thatresearch about an individual’s reasoning process for a commitment and the provision ofcomputerized support of that process are useful and will provide the following benefits: 1) abetter understanding of an individual’s reasoning process in making a commitment, and 2)assistance to individuals in making better justified and more consistent commitments in handlingrequest-commitment problems.1.2 The Goal of the ThesisThe primary objective of this thesis is to develop a domain independent computer-based modelfor supporting an individual’s reasoning process in reaction to a request that requires acommitment. “Agent” is used in this thesis to represent either a human being or an intelligentmachine. We use the word “model “ to mean a general architecture of request-commitmentreasoning support systems. “Support” means that the RECOS model is not proposed as areplacement for a human being to make any commitment at the current stage. Rather, it isintended to provide assistance in determining the related factors to be considered in generatinga response to a request, in evaluating such factors, and in integrating the evaluation result. Inmost cases, the final decision would be left to the user’s discretion. The model focuses onsupporting an individual’s commitment making process in a multi-agent environment. Its scopecovers the process from receiving a request to delivering a response.To achieve such an objective,•commonly related factors for making commitments should be explored, and• the logical structure of the model should be developed.To show the model’s practicality and applicability,• a prototype based on the model needs to be implemented, and•some user trials and evaluations should be conducted.21.3 The Outline of the ThesisThe thesis proceeds as follows. Chapter 2 reviews the related work. Chapter 3 discusses the“commitment” concept in greater detail. Chapter 4 discusses the factors involved in making acommitment and the structure of the model to support the reasoning process. A commitmentconcerns a person’s future behaviour (action). Reasoned action (R-A) theory, which investigatesthe rationale of human behaviours, is also relevant to the commitment making process. Chapter5 probes the relationship between the RECOS model and an R-A theory. Chapter 6 presentssome applications of the model, which includes one sample application using the model and auser evaluation of the model. Chapter 7 reports a prototype based on the model, and the lastchapter discusses the contributions of this work, its limitations and its future research directions.3Chapter 2Related WorkIn this chapter two types of research are reviewed. One is past computer-supported collaborativework based on commitment; the other is research which we believe is related to the RECOSmodel.2.1 Past Computer-Supported Collaborative Work Based on CommitmentSince the early 1980s, the commitment concept has been increasingly used to modelorganizational activities by information systems and artificial intelligence researchers. Theirwork is reviewed in this section.2.1.1 An Early WorkAn early work using the commitment concept to model organizational work is Fikes’commitment-based framework [Fikes 81]. He observes that the primary work of an agent in anorganization is to make and fulfil commitments to other agents. Each agent has a set of functionsto perform. Each function consists of a number of task instances with their preconditions. Whenthe preconditions are met for a task instance, the agent will perform that task. Fikes’ primarythesis is that a commitment to an action is bounded by a set of conditions, but the structure andcontent of the conditions are not elaborated.2.1.2 A Commitment Maintenance Model[Koo 88] presents COMTRAC, a model for supporting agent commitments in a multi-agentenvironment. The author argues that, in organizations, agents cooperate to accomplish certaintasks via commitments. Contracts are used in COMTRAC to record commitments betweenagents, and a contract is represented by a set of terms and qualifications. A term specifies thetasks to be performed, and a qualification defines the conditions that must be met by the timethe tasks are performed. A qualification could be nil, or it could be another term followed by4its qualification. In this way, COMTRAC links all related commitments into a commitmentnetwork, which is called a contract portfolio. When an unexpected event occurs at a node ofsuch a commitment network (e.g., an agent cannot fulfil its commitment as promised orplanned), the related agents need to adjust their commitments to fit the new situation.COMTRAC provides support for this justification process in terms of recording and trackingthe involved agents and commitments. This work does not cover how a commitment is generatedand the rationale of a commitment.2.1.3 A Domain Dependent SystemCoNeX, a project done at the University of Passau, proposes an integrated model for supportinggroup work in software development projects [HaJaRo 90]. It includes three models: 1) a groupmodel specifying the team’s organizations, task definitions, and resource allocations, 2) aconversation model defining a multi-agent communication protocol, and 3) a process modelcontaining software development knowledge and tools. A contract, representing commitments,is used to describe the social agreements on actions. CoNeX provides support to fulfilcommitments (e.g., for a commitment to transform an analysis result into a logical design,CoNeX supplies the user with tools to do the transformation and to evaluate the result), and tomaintain commitments (e.g., tracking which agents are involved in the commitment and thecurrent status of the commitment). However, there is no direct support for an agent’s reasoningprocess for making a commitment.2.1.4 Formal Reasoning on CommitmentA well recognized work of formal reasoning related to commitment is done by Cohen andLevesque (90). They attempt to model the relationships between belief, commitment, and actionusing formal logic. A commitment is defined as a persistent goal. Belief mainly concernswhether the agent believes the commitment is achievable, achieved, or no longer achievable. Therelationship between act, belief, and commitment is that the agent will act to reach the goal untilhe believes that the goal has been achieved, or it is not achievable, or it is not necessary toachieve the goal anymore. For example, when it is raining, the agent may commit to getting anumbrella. He will try to get an umbrella until he believes that 1) he has obtained an umbrella,5or 2) it is impossible to get an umbrella, or 3) the rain has stopped and the action is no longernecessary [Gasser 91]. The agent’s beliefs and commitments must be consistent (e.g., an agentwill only commit to the action that he believes is achievable). Further, an agent not only adoptsa commitment but also believes that he will actually fulfil the commitment. However, how acommitment is established (e.g., factors related to establishing a commitment and motivationsfor an agent to adopt a commitment) is not discussed.2.1.5 An Organizational Model Based on Commitment[Bond 90] models organizational and agent behaviours based on commitment. An organizationis viewed as a set of agents with mutual commitments. A commitment is looked on as aconstraint which binds an agent to perform a course of action, to hold a belief, or to attempt agoal. It specifies some features of commitment. Commitments are social (i.e., a commitmentis a relationship between agents and is based on the trust and expectations of related agents).Commitments require agent integrity (i.e., agent behaviours should be reasonable, predictable,and reliable). Commitments also require resources. More specifically, a commitment is madebased on: 1) the available resources, 2) the expectations of actions taken by other agents andresources supplied by them, 3) the expectation of supplying resources to other agents. As agentsare interlinked through commitments, and each agent may be involved in many of them, the totalcommitments in the system must be integrated and consistent (e.g., all agents should haveconsistent beliefs under the same context and time interval). An Agent’s commitments to allother related agents should be consistent with those agents’ expectations of him. Theseguidelines are useful for modelling multi-agent systems based on commitments. However,regarding how a commitment is made by an individual, this work mainly concerns theconstraints that a commitment must meet and resources that are needed to fulfil the commitment.Very little is mentioned about an agent motivation for making a commitment.2.2 Other Related WorkSome research in the field of artificial intelligence and information systems, such as competenceassessment, negotiation, and belief reasoning, were not built for modelling commitments.6However, we observe that the principles and results in this research could be beneficial to ourwork, so, we will briefly discuss it in this section.2.2.1 Competence AssessmentThe essential idea of the competence assessment [V0KaDL 90] is to estimate the solvability ofthe problem and the agent’s capability to solve it before an agent actually solves the problem.The requirements for solving the problem and the match between the requirements and theavailable resources are major issues in evaluating the competence of an agent. Although ageneral method for conducting such an assessment is not yet available, the ideas presented inthis research can be used in the RECOS model.2.2.2 Negotiation“Negotiation is a form of decision making in which two or more parties talk with one anotherin an effort to resolve their opposing interests.” [Pruitt 81, p.xi]. When an agent makes acommitment, negotiations will very likely occur as the requester and the responder may havedifferent interests. A lot of work has been done on negotiation, but we will not discuss it atlength in this thesis. Interested readers are referred to [ChaWoo 91]. A detailed negotiationprocess is beyond the focus of the RECOS model. However, the initiatives of a negotiation andthe results from the negotiation should be considered when an agent makes a commitment.2.2.3 BeliefAn agent’s beliefs are opinions or conditions held by the agent about the environment, otheragents, or himself [Konoli 85]. Thus, belief is subjective. Something believed by an agent maynot necessarily be true. In intelligent systems, an agent’s beliefs and his reasoning mechanismsare normally separated from domain dependent problem solving mechanisms. A belief subsystemusually includes a set of basic beliefs which are called explicit beliefs, and a set of beliefinference/derivation rules. From the basic belief set and the inference rules, some results, calledimplicit beliefs, can be derived. A belief system must be consistent, i.e., it should not believeboth A and not A, explicitly or implicitly. Otherwise, meaningless results would be produced.7There are primarily two kinds of requests which need a belief subsystem’s attention [Konoli85]: 1) given a statement, query the belief system to find out whether it should be believed bythe agent; 2) since the basic beliefs or the inference rules could be wrong, when any of themor a derivation of them conflicts with new knowledge or fact, revise the belief system tomaintain its consistency. We call the first issue “belief reasoning” and the second “beliefrevision” or “belief maintenance”. There is extensive research in each of these two fields.Interested readers are referred to [Konoli 85, GenNil 87, McArth 88, Doyle 79, DeKlee 86, andMasJon 89]. The RECOS model will not look into any specific belief reasoning or beliefmaintenance mechanisms. However, the research results from this area can be applied toimplementing the RECOS model because people make commitments based primarily on theirbelief systems.2.3 SummaryIn the past decade, people have tried to model and support collaborative work based oncommitments. This suggests a new research direction, and, hopefully, sets up a new foundationfor information systems and distributed artificial intelligence research [Hewitt 91]. We believethat the trend is plausible, and, in particular, researchers have turned their attention to sociologyand other social sciences. An organization is a small society that should be studied using socialscience theories such as sociology and social psychology.We share the belief with Fikes (81) and Bond (90) that agent mutual commitments linkorganizational activities together and get tasks accomplished. We also share the belief withFlores and Ludlow (80) that making, maintaining and implementing commitments constitutes alarge percentage of organizational work. Unfortunately, very little work has been done in thearea of studying and supporting an agent’s reasoning process in making a commitment. Webelieve that the major difficulty is that there are a lot of uncertainties in making a commitment,and the reasons behind a commitment can be quite complicated or context dependent.Although it seems impossible to build a fully automated commitment handling system, we8observe that there are still some commonalities in making a commitment. For example, certainfactors are always considered and evaluated when a commitment is being made (e.g., resourcegains and losses, interpersonal relationships between the involved parties). Motivated by thisobservation, we attempt to solicit these factors and to explore the possibility of using them inbuilding a reasoning framework for making commitments. This is done by developing acomputer-based model for supporting an agent’s reasoning process in reaching a commitment.9Chapter 3CommitmentCommitment is a fundamental concept in the RECOS model. In this chapter we will provide adefinition of the concept of commitment, review sociological research about commitment, anddiscuss the relationships between commitment and other related concepts.3.1 The Commitment ConceptWebster’s Dictionary [Gove 67] defines commitment as: “1. the act of doing or performingsomething; 2. a) the obligation or pledge to carry out some action or policy or to give supportto some policy or person; b) the state of being obligated or bound.” The second definition,which emphasizes the binding and constraining of someone to something, is widely used insociology and social psychology [Gerard 68, Kiesle 71, Brickm 87, Becker 60, and Gerson 76].This definition has also been accepted by information systems and artificial intelligenceresearchers [Bond 90, Koo 88, Hewitt 91, Gasser 91]. Adapting this definition of commitmentfor our purposes (i.e., responding to another agent’s request), we define commitment as anagreement by an agent to the requester in carrying out the requested action. As soon as acommitment is made and delivered to the requester, the committed agent is bound by it. Acommitment should be fulfilled in accordance with the agreed upon terms unless the requesterwithdraws his request or fails to meet his responsibility, or the involved parties agree to modifythe terms or cancel the agreement. On the other hand, when the requester receives thecommitment response to his request from the other agent, he will also automatically be boundby the terms presented in his request unless some further negotiation takes place. In this thesis,‘commitment’ refers not only to an agreement to carry out the requested action but also thefulfilment of it.A commitment does not always involve multiple agents. A person may commit himself to acertain cause or goal (e.g., one may commit to spreading the Gospel or to pursuing a graduate10degree) [Brickm 87, Bond 90]. In this case, the commitment may not be stimulated by anexternal request and no other agents are directly involved. We consider this type of commitmenta personal commitment, and it is a special case of the definition given in this section.3.2 Commitment from the Sociological PerspectiveCommitment has been studied in sociology for a long time. Organizational commitment study,an area investigating the factors that contribute to bind a person to an organization, has enjoyedmuch attention from sociologists.A well known discussion on commitment is Becker’s “side bets” notation [Becker 60]. In hisopinion, one’s commitment to an organization is determined by the rewards and costs (side bets)associated with the organizational membership. Becker concludes that a person’s commitmentto an organization could be determined by his previous commitment to the firm’s pension plan,by others’ expectations that he will not change companies too often, or by his investment (e.g.,experience) in the organization. Another point made by Becker is that the effect of the relatedfactors on a person’s commitment is determined by the individual’s own value system.Becker’s side bets argument on commitment has been supported by a number of empiricalstudies. Alutto et al. (73) did a survey with a sample of 318 school teachers and 395 hospitalemployed nurses. The findings suggest that individual organizational transactions and the accrualof side-bets or investments are crucial to an understanding of the commitment phenomenon.Mattaz (87) conducted an empirical study on the relationship between work satisfaction andorganizational commitment. He found that it is not job-tenure that produces greatercommitment, but high levels of rewards and satisfaction, which are correlated with tenure.Sayeed (89) analyzed data collected from 204 managers, and his results indicate that the longeran individual has been with an organization that has good fringe benefits, cordialmanagement-subordinate relationships, and positive organizational policies, the greater the levelof commitment and the period of attachment to the organization.11Becker’s and others’ findings have general implications, i.e., a commitment to something isusually constrained and motivated by rewards and costs associated with such a commitment. Aperson’s previous commitments (i.e., side bets), play an important role in identifying theserewards and costs.Gerson (76) furthers the study of commitment by extending Becker’s work. Several points fromhis work are worth mentioning. First, a person participates in different settings viacommitments. His commitments in all settings are interlinked and thus form a commitmentpattern, which Gerson calls sovereignty:“I shall call the overall organization of commitments associated with any delimitable socialobject the sovereignty of that object.” (p.798).Assuming that people behave consistently, making a new commitment or changing an existingcommitment should be consistent with this commitment pattern. Thus, to understand anindividual’s commitment behaviour, one should not isolate a specific situation but should takehis commitment pattern into consideration. Second, a commitment can be represented byresources invested and produced. “Participation in any situation, therefore, is simultaneouslyconstraining, in that people must make contributions to it, and be bound by its limitations, andyet enriching, in that participation provides resources and opportunities otherwise unavailable.”[Gerson 76, p.’797]. Finally, resources can be classified into categories: money, time/schedule,skill, and sentiment. The details of the resource categories will be discussed further in section4. A Formulation of CommitmentWand and Woo (91) define commitment using concepts from Bunge’s Ontology [Bunge 77,Bunge 79]. Ontology is a branch of philosophy dealing with models of the world. According tothis theory, everything in the world at a given time has a state (stable or unstable), and thetransition from an unstable state to a stable state is guided by transition laws. Commitment isdefined by the pair <unstable state, transition law>. A thing in a stable state will assume anunstable state only as a result of an external event. Thus, an external event serves as both a12trigger to and the input mechanism for a commitment to be undertaken. Conceptually, our modelfits this formalization well. More specifically, an agent can be viewed as a thing. A requestfrom another agent is an external event to the agent, and the rationale to commit or reject therequest can be looked at as transition laws. Rejecting a request or committing to a request(followed by the execution of the commitment) would put the agent in a stable state. RECOS’focus lies in exploring the major factors to be considered by the transition laws for makingcommitments and in supporting an agent in the evaluation of these factors.3.4 Commitment vs. DecisionDecision and commitment are closely related concepts. According to Webster’s Dictionary[Gove 67] decision has two basic meanings: (1) the act of deciding, and (2) a determination orconclusion arrived at.Conceptually, there are some differences between commitment and decision. Commitment isa concept which stresses an agent’s persistence in doing something, and it lasts for a certainperiod, usually until the commitment is fulfilled. Decision (as an act of deciding) occurs at aspecific point in time. Commitment emphasizes an agent’s obligation to something, or beingbound to something. As Gerard [68] points out, commitment is irrevocable. A decision (as aconclusion arrived at) may not be so. Frequently, people make arbitrary decisions but are notserious about them, so often fall to fulfil what they have decided. “Only those decisionsbolstered by the making of sizable side bets will produce consistent behaviour. Decisions notsupported by such side bets will lack staying power, crumpling in the face of opposition orfading away to be replaced by other essentially meaningless decisions until a commitment basedon side bets stabilizes behaviour.” [Becker 60, p.38].Decision and commitment are, however, closely related. If the decision-maker is expected tocommit to what he decides, such an expectation will produce a warning effect for the decisionmaker when a decision is being made [JanMan 77]. As mentioned in section 3.2, the decisionmaker’s commitment pattern will constrain his decision on a related issue. For example,13committing to take care of his father might lead to a person’s decision to live with his father,or committing to buying a house might motivate a person to save money for a down payment.Nevertheless, according to the definition of commitment used in this thesis (section 3.1), thereasoning process that RECOS intends to support is a specialized decision-making process, whichbasically deals with a binary decision-making problem (i.e., agree or not to carry out therequested action) and the requested action is predefined. For example, “Would you join us forthe party tomorrow?” is a binary decision-making problem; it has a clearly defined action (cometo the party), and the decision would be “yes” or “no” to this request. On the other hand, ageneral decision-making problem could be much more complex and the alternatives for choicecould be numerous. For example, “How much should I spend on entertainment if I win a$10,000 lottery?” is not a binary decision-making problem because it could have numerousalternatives (spending $0 to $10,000 on entertainment) rather than “yes” or “no”to choose from.From this discussion we see that the request-commitment problems that RECOS proposes to copewith is better structured than, and a sub-set of, general decision-making problems. Therefore,we call RECOS a request-commitment support model rather than a general decision supportmodel. In order to make a consistent and better justified commitment, research results ofcommitment study (e.g., sentiment and commitment interlinks) should be considered.3.5 Commitment vs. ContractAnother related concept to commitment is contract. Contract is defined as “an agreementbetween two or more persons or parties to do or not to do something.” [Gove 67]. It is a widelyused term in law, sociology, and economics [Macnei 80, BarOuc 86].The commitment concept (see section 3.1) used in this thesis is closely related to the concept ofcontract as it is defined above. The request receiver commits to carrying out the specified actionand the requester commits to the terms, if any, described in the request. These tightly boundcommitments make up a contract.14In terms of work done in the area of contracts, Macneil (80) characterizes a number of factorsrelated to contractual relations. Because of work specialization, people perform utilityexchanges. However, he claims that contractual relations are not simply economic relations butalso personal relations. Furthermore, contractual relationships usually involve many people andrequire role integrity (i.e., contracted parties should behave consistently and in a predicableway). It is a relationship of cooperation, and the involved parties need to share and divide thebenefits and burdens. The power of involved parties would affect contractual relationships. Acontract has a binding effect, and the involved parties are obliged to fulfil the contract.Some of these factors (i.e., role integrity, binding effect, agent cooperation, and multi-partyinvolvement) will be taken as assumptions in RECOS. The others will be directly reflected inthe RECOS reasoning framework. In other words, R.ECOS is consistent with the theory ofcontractual relations.We call the RECOS model “commitment support” rather than “contract support” for thefollowing reasons: 1) it focuses on the reasoning process of the request receiver; 2) it isprimarily based on commitment research results (e.g., the resource perspective of commitmentand the commitment consistency viewpoint) which, we believe, provide better insight into anindividual’s commitment behaviour, and can be directly used for modelling agent’s commitmentactivities, but which are not readily available or are only described on a very conceptual levelin contract study; and 3) although modern contractual relations have a more general meaning,they originate from economical exchange [Macnei 80]. When people think about a contract, theymay still consider it in economic exchange terms. However, the commitment concept emphasizesthe sentiment factor, which is essentially different from a contract based on economic exchangeterms.3.6 SummaryIn this chapter, we have defined a commitment to be an agreement to carry out the requestedaction. Such an agreement is not arbitrary, but will bind the committed agent to fulfil the15specified actions. Thus, a commitment must be based on solid reasoning and justification inorder to reduce post-commitment regret or revocation. A reasoning process for establishing acommitment is primarily a decision-making process, which features commitment characteristics.From the discussion, we conclude that, in order to make a well-grounded commitment to arequest, “side bets” and other related factors must be evaluated before a commitment is made.16Chapter 4RECOS: A Request-Commitment Support ModelIn previous chapters we have discussed that one type of agent cooperation can be representedby the pair <request, commitment>. When an agent receives a request to carry out a certainaction, he must evaluate the related factors, and figure out whether or not he should commit tothe requested action. To assist an agent in making a well justified commitment, there is a needto develop computer-based systems for supporting such a reasoning process. In this chapter wewill present one such model. First, we clarify the boundaries of the model; next we proposea set of common factors related to handling requests that require commitments; then, we proposethe model; and finally, we conclude the chapter with a discussion of the model.4.1 Boundaries and Assumptions of the Model4.1.1 BoundaryRECOS supports an individual’s reasoning process from the time of receiving a request to thetime of delivering a response with the RECOS model. In other words, it does not supportcommunication between agents. Only the input to and output from the communication areconsidered.RECOS is not intended to replace the user at the current stage. Rather, it is aimed at assistingthe user to select factors for consideration, and to evaluate these factors. It also attempts toprovide some support in integrating the results of the evaluations.During the reasoning process, many types of knowledge will be required (e.g., past experience,organizational regulations, etc.). RECOS embraces these types of knowledge bases and proposestheir basic contents. However, the detailed internal structure of these knowledge bases is notfully explored; only the interfaces with them are considered.17RECOS extracts a set of factors into its reasoning framework. This is basically done by applyingresults from the related literatures discussed in chapter AssumptionsRECOS is built on, or can be best used, under the following conditions:1. Agents are consistent and trustworthy. “Consistent” means that agents committing or notcommitting to a request will not prohibit the fulfilment of existing commitments. Forexample, an agent will not commit to physically attending two separate meetings at thesame time. However, if a decision would result in such a prohibition, the affectedcommitments should be adjusted (e.g., to negotiate with the involved agents to modify theaffected commitments) when the decision is made. “Trustworthy” means that agents canbe depended upon to fulfil their commitments. This enables an agent to act (e.g, carry outcommitments and make new commitments) based on his own previous commitments andother’s commitments to him.2. Agents are rational, that is an agent will not commit to a request without good reasons forsupporting it. Thus, the evaluation of the relevant factors is useful for making a decision.3. An incoming request is readily interpretable by the receiver (i.e., either agents sharethe same language or the incoming request has been translated accurately into the languageused by the receiver).4.2 Factors Related to CommitmentsAs discussed in chapter 3, a commitment is determined by the costs and rewards associated withit. In order to reduce post commitment regrets, and to maintain individuals and the system ina healthy state, an agent must evaluate related factors to make a well-grounded commitment. Inthis section, we discuss these factors in detail. As the model is intended to handlerequest-commitment interactions in an organizational environment, factors such as organizationalregulations, relations between the requester and the receiver will also be explored, in additionto the factors revealed in commitment research.184.2.1 ResourcesA commitment will bind an agent to a certain course of action. As pointed out by Gasser (91),to carry out such an action the committed agent needs to invest resources: “We can see acommitment as simply the use of resources.”(p.l29).Resources can be anything that is neededfor, or is affected by, completing a committed action. They can generally be classified intoseveral categories: money, time/space/material, skill/mechanism/technology, and sentiment[Gerson 76, Hewitt 91]. An action may not demand all of these resources, but one or more isneeded in the implementation of an action.Of these types of resources, money and time/space/material are self-explanatory. Skill refers tothe ability of a person to perform a task or action. This may range from the technicalrequirements of a particular job to social management skills. Mechanism/technology includestools, equipment, and know-how. In this thesis, skill refers to both the skill andmechanism/technology mentioned above. Sentiment is “an attitude, thought, or judgementpermeated or prompted by feeling.” [Gove 67]. It includes affection, loyalty, respect, esteem,or honour. It also includes reflective sentiments such as guilt, shame, embarrassment, goodwill,or reputation. Sentiment is considered a resource because carrying out certain actions mightrequire certain types of sentiment. For example, helping a person who has failed several timesto get back on track requires someone who is affectionate towards and respected by the person.Certainly, not everyone is qualified to be a helper. Therefore, the sentimental attributes of thosewho can help are considered to be their resources. In addition, sentimental values, like otherresources, can increase or decrease. For example, a person who successfully helps others maygain more respect from them.Sometimes, the resources could be convertible from one form to another, e.g., money might beexchangeable for material and skills. In these cases, we need to avoid double counting the samecomponent. In addition to the basic types of resource, another kind of resources is commitmentsfrom other agents; these commitments can be directly or indirectly converted into the basic typesof resources described above. As money, time/space/material, and skill are either quantifiableor testable, we call them tangible resources. Sentiment is an intangible resource.19It is worth pointing out that a commitment may not only require the committed agent’s resourcesbut also the resources of others. For example, committing to an out-of-town project may notonly require the agent’s time, but also other family members’ time to take care of additionalresponsibilities while the agent is out of town.4.2.2 Requester, Inter-agent Relationship, and Others’ ExpectationsAs commitment in RECOS pertains to agent interactions, the merit of the requester and therelationship between the involved parties might influence the agent in whether or not to committo a requested action. There could be many requester’s properties which might affect the agent’sdecision about a commitment, such as reliability. In this thesis we use the word “credibility” asa general term to represent the major properties of the requester, which might affect the agent’swillingness to associate with the requester via a commitment to the request. In terms of therelationship between the requester and the agent, it can be measured in two dimensions: 1) thevertical (i.e., relative power levels between the involved agents, where power means the abilityto impose one’s will on others; this can be political, economical, or social [Macnei 80, Simon57]); and 2) the horizontal (i.e., close/remote). Requests from agents with different relationshipswith the receiver would carry different levels of strength, and thus, would usually be dealt withdifferently.In addition to the relationship between the requester and request receiver, the request receiver’sclosely-related agents (e.g., familymembers, supervisor, colleagues,friends, etc.) may havesome expectations about the commitment. An agent’s commitment “would be a function of suchthings as his awareness of the expectations, the characteristics of his relationship with those whohold the expectations, and the perceived legitimacy of the expectations.” [Johnso 73, p.39’7].These expectations can be explicit or implicit (e.g., someone explicitly expresses his approvalor disapproval of one’s commitment to a request), and may or may not be connected withresource gains/losses depending on the situation and the agents involved.4.2.3 RegulationsAccording to the social rule system theory [BurFia 87, pp.54-55], “an institutionalized rule20system, a rule regime, is a system of rules adhered to by actors in a particular group,organization, culture or society.” It plays an important role in guiding and regulating socialactions and interactions of agents in organizations. Because agents supported by RECOS are inorganizational settings, their behaviours should be guided by their organizational rules orregulations. In RECOS, regulations is a general term used to represent laws, rules, procedures,or conventions in the organization. Some regulations might be mandatory, and therefore, mustbe followed by the affected agent; others might be suggestive and flexible.4.2.4 Commitment ConnectionsAccording to Becker’s side-bet [Becker 60] and Gerson’s sovereignty perspectives ofcommitment [Gerson 76] (both discussed in Section 3.2), an agent participates in multiplesettings and has many commitments to fulfil. These commitments are not isolated from eachother, but linked together. Because of the inter-commitments relationship, previouscommitments will restrict an agent’s options to the current request. As pointed out by Payneand Elifson (76), once an agent is committed to a certain line of action, some formerly availablelines of action are closed. Discontinuing a committed line of action would result in certain costto the agent. Johnson (73) labels this type of cost as “cost commitment”. Thus, the relationshipbetween the current request and the agent’s previous commitments would play an important rolein determining his committing or not committing to the requested action.Distributed Artificial Intelligence (DAI) research has further elaborated this point. Gasser (91,p.114) points out that “commitment of A (i.e., continued participation of A) in a course ofaction in any particular setting is a product of the interactions among its simultaneousparticipation in many other settings.” He also mentions that “commitment in this sense is theoutcome of a web of activity.” Although Gasser makes this statement when discussing jointcommitment among multiple agents, its underlying meaning is clear: commitments areinterlinked, an agent’s commitment to a particular situation is affected by his othercommitments.According to Gerson (76), Gasser (91), and Hewitt (91), commitments are usually linked via21resources. The commitments which share the same type of one’s resources (e.g., time) arelinked together by that resource. We observe that there is another type of connection amongcommitments, which is different from resource sharing. That is, commitments could be linkedby a predefined term or relation (e.g., if an agent is committed to work exclusively for acompany, accepting a job offer from another company would directly conflict with his previouscommitment). In this thesis, these two types of commitment connections are called indirect anddirect connections respectively. In both direct connection and indirect connection, the previouscommitments will constrain an agent when considering a commitment to the new request, butin a different manner. The resolution of the conflict may also be different. For example, ifthere is a conflict in using shared resources and the agent wants to commit to the currentrequest, then either the resources committed in the previous cases must be revised, or theresources required for the current request needs to be negotiated. Similarly, if there is a directexclusive connection between a previous commitment and the current request, either the currentrequest might need to be rejected or the previous one revoked. In RECOS, these two types ofrelationships are dealt with separately. Resource conflicts are handled in “Competence”Assessment and direct linkages are looked after in “Commitment Consistency” Assessment. Bothof these assessments will be discussed in section Dfrect Gains/LossesAny commitment involves a positive side and a negative side. The bond of these two sides willdetermine an agent’s commitment [Brickm 87]. In RECOS, we use the words “gains/losses”as a general term to refer to the net positive/negative effects of a decision (e.g., commitmentor rejection) regarding the request. The gains/losses are measured in terms of resources. Acommitment to a request may produce both gains and losses of different types of resourcesbecause the resources involved may not be comparable. We use “direct” to mean that this typeof gains/losses is directly linked to the request without any interference from other factors (e.g.,regulations, other commitments, and others’ expectations). For example, a commitment to pickup someone at the airport, which results in being paid $20 by the requester, signifies a directgain in money. The gains/losses are classified into two categories: tangible and intangible. Thetangible gains/losses are gains/losses in money, time/space/material, and skill. The intangible22gains/losses are gains/losses in sentiment. A commitment may not only produce gains/losses forthe committed agent, but also for other related agents. For example, committing to a companymay not only benefit the agent, but also his family. For a professor to sit on the editorial boardof an international journal not only enhances his or her reputation, but also reflects on the schoolwhere he or she is employed.It is clear that committing to a request usually involves gains/losses. On the other hand, rejectingthe request may also have gains/losses. For example, a request may have an attached term: ifyou commit, you will be rewarded with $1,000; if you do not commit, you will be punished bya $500 fine. This $500 loss cannot simply be added to commitment gains, since the effect mightbe different. Thus, when one evaluates the gains/losses related to the request, it is important toconsider the gains/losses for both commitment and rejection.4.2.6 BeliefsA commitment to an action is usually made before actually undertaking such an action. Thus,a commitment is usually based on estimations (i.e., beliefs about and/or expectations to thecommitment environment, self, and related agents). Similar to Bond (90), we use belief torepresent both what an agent thinks he knows about the past, and his expectations of the future.4.2.7 SummaryBased on some sociological research on commitment (i.e., Becker’s side-bet [Becker 60],Gerson’s sovereignty [Gerson 76], and Johnson’s cost commitment perspectives [Johnso 73]),DAT research about commitment (i.e., commitment connection and resource viewpoint ofcommitment [Gasser 91, Hewitt 91]), the social rule system theory [BurFla 87], and a contracttheory [Macnei 80], RECOS takes the following factors into its reasoning framework for anagent making a commitment: 1) resources, including money, time/space/materials, skills,sentiments, and others’ commitments; 2) requester, inter-agent relationship, and other’sexpectations; 3) direct gains/losses associated with the request, which can be further divided intotangible and intangible gains/losses; 4) regulations; and 5) the relationships between the currentrequest and the agent’s other commitments (i.e., commitment connections).23We recognize that the above mentioned factors are not necessarily mutually exclusive.Forexample, the expectations of related others and organizational regulations mayalso affectresource gains/losses. However, the factors other than direct gains/losses mayalso play anindependent role in affecting the agent’s decision. Therefore, they deserve separate treatment.Sometimes these factors might imply resource gains/losses but in an indirect manner. Webelieve that by separating these factors from the direct resource gains/losses, the agentwill bebetter able to structure the rationale for the commitment, and will gain betterinsight into thatrationale. As long as the user is aware of potential overlaps and tries to avoid counting thesamefactor more than once in different categories, the potential problemwill be eliminated orminimized. We also notice that this set of factors is by no means exhaustive. Thesefactors areused because we believe that they are most relevant and are also contextindependent. If onecould make his commitment based on the evaluation of these factors, the commitment would bebetter justified.4.3 The RECOS ModelThe RECOS model is developed to support an individual’s reasoning processin handling arequest that requires a commitment. This is done by assisting him in selecting andevaluatingthe factors proposed in section 4.2, and in integrating the evaluation results. In this section, wewill present an overview of the model, discuss the knowledge bases used in the reasoningprocess, and look into the components of the reasoning process. As we havediscussed in theprevious section, agent commitments are based on his beliefs about himself (e.g., skills), aboutothers (e.g., Agent B will commit $10,000 to a project), and about the commitment environment(e.g., the recession is not over yet). Belief(s) could be applied to many of theknowledge basesand to the reasoning components, which will be described in sections 4.3.2 and4.3.3.However, whether something is a belief or a fact is application dependent, and it is, therefore,left as part of the design considerations for system developers to consider.4.3.1 Overview of the ModelFigure 1 shows the overall logical structure of the model. The RECOS model includes a24Legend:Agent or userExecution flow orUser/Agents InteractionCZ)Process ModuleKnowledge Base AccessKnowledge Base - - - -- Evaluation Result SharingFigure-i: RECOS Model Structure and Reasoning Framework250OtherAgent(s)Kequesterand/or otheragent(s)preprocessing module, several factor evaluation modules, and anintegration module. Duringthe reasoning process, each module may need to access various knowledge basesto carry outthe specified functions. These knowledge bases are currently treated as “black boxes”.Only theinterfaces between the boxes and the reasoning mechanism areconsidered. Because both theknowledge bases and processes are the critical components of themodel, we will discuss themseparately in the following sections (sections 4.3.2 and 4.3.3).4.3.2 Knowledge BasesAs mentioned above, various types of knowledge may be used by an agentin his reasoningprocess to reach a commitment (see section 4.3.4). These types of knowledge aremaintained inthe following knowledge bases.1. Topic Base: consists of all topics about which the agent has some entries ofknowledge.2. Agent Base: includes two types of information:1) major properties of the agent (e.g., position in the organization, etc.);2) major properties of other agents (e.g., skills, credibility, position in the organization)andtheir relationships with the agent.3. Expectation Base: contains perceived expectations of relatedothers about the agent’scommitment to certain requests.4. Case Base: comprises the accumulated request handling experience of theagent. Itscontents are various commitment cases. Each case consists of elementsclosely related toa commitment, such as the relationship between the involved parties, therequirements forfulfilling the commitment, tangible and intangible gains obtained, etc.Techniquesdeveloped in the area of case-based reasoning (e.g., case representation andindexing) areapplicable [Kolodn 88, Hammon 89].5. Organizational Knowledge Base: contains organizationalinformation that is useful to theagent in his reasoning process. Its components are:1) Regulations and procedures related to a particular task or position2) Organizational structure which describes the structure of the organization andrelationshipsbetween organizational positions.266. Resource Base: contains information related to:1) tangible resources that are owned by or are accessible to the agent (e.g., skills, time,space, etc.), or are committed to the agent by others (pick you up at the airport).2) tangible resources allocation and availability information.3) intangible resources, i.e., sentiment attributes, possessed by the agent.7. Commitment Base: includes the agent’s commitments, which are being executed or arewaiting to be executed. The major components are: the identity of a commitment (e.g.,topic), related agent(s), resources committed, tangible/intangible gains agreed uponorexpected, connections with other commitments, etc.8. Quantitative Model Base: consists of operations research, econometrics, and otherquantitative models for evaluating gains/losses.9. Decision Rule Base: includes basically two types of rules in this knowledge base. One isuser predefined responses to certain requests from certain agents. The other is rules forusing or integrating the factor evaluation results. Becker (60) states that one’s commitmentis affected by the value system which influences one’s behaviour. Theinfluence of sucha value system will typically appear at the integration stage and will be reflected inthe“decision rule base”.The knowledge in various knowledge bases can be retrieved through queries. A general querywould look like: query_name(Condition_of_the_query, Knowledge_items_to_be_retrieved).4.3.3 Components of the Reasoning ProcessIn this section, the functions of individual processes (shown in Figure 1 as ovals) of the RECOSmodel are discussed. The process components can be classified into three types according totheir roles in the reasoning process: preprocessing, factor evaluation, and integration. Theindividual component functions are described below.The preprocessing determines whether it is necessary to go through the detailedevaluationprocess, and whether the system has any knowledge of handling such a request.This is done byconsulting the “topic base” and the “decision rule base”. In the case where the requestisunknown to the system, a user’s involvement in making the decision is needed.27Factor evaluation, the major part of themodel, consists of the following factor evaluationprocesses:1. Requester, inter-agent relationship, and others’ expectations assessment: Thisprocesscollects information about the requester, the relationship between the requester and theagents, and others’ expectations of the agent’s decision about the request, usingtheknowledge in the “agent base”, “organizational knowledge base”, “expectation base”, and“case base”. “Organizational knowledge base” is consulted because the organizationalstructure may provide useful information in determining the relationship between the agentand the requester.2. Regulation assessment: This process collects informationfrom the “agent base”,“organizational knowledge base” and “case base” on the organizational role of the agentin handling the request. The “agent base” is consulted since that is where theagent’s statusin the organization is stored.3. Commitment consistency assessment: This process determines the direct commitmentconnection (Section 4.2.4) between the current request and theagent’s other commitments.If there is any such connection, the process willalso assess the consequences if theconsistency is violated. This component willaccess the “commitment base” and “casebase” to accomplish its functions.4. Competence assessment: In terms of theresources available to the agent and his othercommitments, this process evaluates his capabilityto perform the requested action. Inorder to assess the agent’s capabilityto fulfil the commitment, the basic requirement of thecommitment needs to be estimated first. Thus, in this module, there are two majorfunctions: 1) to estimate the commitment requirement, and 2)to assess the agent’scapability to fulfil the commitment. The evaluation is done by consulting the “case base”,“resource base”, “commitment base”, and “agent base”. The “commitment base” and the“agent base” are consulted because some other commitments may need to be modified, orothers’ commitments are needed in order to access or acquire the required resources. Ifthis is the case, the consequences of doingso will also be assessed.5. Direct gains/losses assessment: This process identifies the direct resource gains/lossesassociated with the request. This is done by consulting the “case base”, the requirement28output from the competence assessment, and the information from the requester. Whenpossible, the quantitative model may be used for evaluating tangible gains/losses.Note that it is not necessary to go through all of the abovefactor evaluation processes to makea decision, and that there is no particular sequence that one must follow in using these processes.However, as a default, the competence assessment needsto be done before the directgains/losses assessment, since the latter may need some requirement information generated inthe former. During the factor evaluation, if the systemdoes not know anything about a specificfactor related to the request, the user will be consulted.The last component of the reasoning process is integration. Thisprocess will integrate all resultsobtained from the above evaluations, and try to make a recommendation to the user along withthe rationale. In the case where the system cannot make a recommendation, all evaluationresults will be presented to the user for his judgement. If the request needs support from otheragents, if a previous commitment needs to be changed in order to accommodate the request (i.e.,indirect commitment connection mentioned in Section 4.2.4), or if the details of the request(e.g., resource usage, tangible reward for the commitment, etc.) need to be worked out withthe requester, then the integration process will present the relevant informationto the user, andwait for feedback before taking on the actual negotiation with other agents.The result of thenegotiation will be used as new input to the integration process for makinga finalrecommendation. After a reply is made, the system updates its knowledge bases(e.g., “resourcebase”, “case base”, etc.) to reflect its state and knowledge gain from the user in the reasoningprocess.4.3.4 SummaryGenerally speaking, to reach a decision about a request, an agent needs to go through the threestages: preprocessing, factor evaluation, and integration. During the reasoning process, theinformation transfers from preprocessing to factor evaluation to integration. Also, informationflows between process components and knowledge bases. All of these information retrievals andtransfers make the reasoning process possible. The information input and output to and fromeach process component, and the association of processing components and knowledgebases are29summarized in Table 1.Module Input Output Knowledgebase(s)accessedPreprocessmg Incoming 1. Direct response to the request. Decision rule base;request 2. Go on to the factor evaluation. Topic base.Requester, Incoming 1. The credibility of the requester. Agent base;Relationship, and request 2. Relationship of the agent and the requester. Expectation base;Others’ 3. Expectations of related others about the OrganizationalExpectations agent’s decision. knowledge base.Regulations Incoming 1. Relationship of the regulations and a decision Agent base;request on the request. Organizational2. Possible consequences of not complying with knowledge base.the regulation, if there is any conflict.Commitment Incoming 1. Nature of the connection (e.g., exclusive, Commitment base.Consistency request inclusive, no connection, etc.).2. If there is a connection, commitments affectedby the decision on the current request.3. If there is a connection, the estimatedconsequences if the decision is taken.Competence Incoming 1. Requirements for fulfilling the commitment. Agent base;request 2. Competence status: a) competent; b) modify Commitment base;previous commitments; c) need others’ Resource base.commitments; d) not competent. In cases of b),c), and d), the reason will be specified; in caseof b) and c), the potential consequences will bespecified.Direct Incoming 1.Direct gains/losses for self if commit. Quantitative modelGains/losses Request; 2.Direct gains/losses for related others if base.Require- commit.ment 3.Direct gains/losses for self if not commit.Information. 4.Direct gains/losses for related others if notcommit.Integration Incoming 1. Commit. Decision rule base.request; 2. Reject.Factor 3. Negotiate.Evaluation 4. Issue request(s) to other agent(s).Results.Note:1. “Case base” is associated with all modules.Table 1. Summary of the Information Flow in the RECOS Model304.4 DiscussionWe have presented RECOS in this chapter. Now we briefly discuss its major features and itsrelationships with traditional decision support systems and scheduling systems.4.4.1 A General and Flexible Reasoning FrameworkThe model provides a reasoning framework for making commitments. Given the factors includedin the model, we believe that it can provide support to a wide range of request-commitmentproblems. A reasoning process does not necessarily include all steps covered by the model, noris the sequence of steps fixed in terms of the factor evaluation. This gives the user flexibility inhandling real world problems.4.4.2 AdaptabifityWhen the system receives a request, it will first try to handle the request automatically bychecking relevant knowledge bases. In some instances, the job will be done automatically. Forexample, when the user does not want to consider certain requests (e.g., paper review fromcertain agents), the system can reject all requests that fall into this category. In this case, thesystem is similar to the work presented in [MaGLRR 87]. If the above attempt fails, and the userneeds assistance, then the system will use the model’s reasoning structure to assist him/her. If,at any step of the reasoning process, the system does not have the required knowledge, the userwill be consulted. Thus, the system is able to handle a variety of tasks including ones for whichit has thorough knowledge, or those for which it has no knowledge at all. Even when the systemdoes not have knowledge about a specific request, its reasoning framework may still be usefulfor the user to structure his reasoning process.4.4.3 Relationship of RECOS and Scheduling SystemsScheduling is the process of devising or designing a procedure for a particular objective andspecifying the sequence or time for each item in the procedure [NorSar 91]. Based on thisdefinition, scheduling problems always involve some objectives, multi-activities, time, andsequence. The RECOS model has some overlaps with the scheduling system as it is defined31above, in the sense that RECOS includes scheduling as part of its functions. However, themodel’s major focus is not on the scheduling problem, but on commitment reasoning, i.e.,whether the agent should or should not make the commitmentto the request. In this sense, themodel is mainly concerned with thedecision. Usually, a scheduling system focuses on how tomanage or schedule the activities to fulfil certain goalsor constraints and assuming the decisionas a given. In the RECOS model proposed in this thesis, the scheduling function is takenas aprerequisite condition for commitment. If the requested task cannotbe scheduled, the system willnot commit to the request. But, even if the task canbe scheduled, the agent may still not committo the request due to other unfavourable factor evaluation results.4.4.4 Relationship of RECOS and Traditional Decision Support SystemsIn section 3.3, we claimed that the reasoningprocess for establishing a commitment is aspecialized decision-making process. For this reason, RECOS can be viewed as a decisionsupport (DS) model focusing on improving both the efficiencyand effectiveness ofdecision-making in the agent interaction and cooperation domains. When dealing with routinework with which the system has thorough knowledge, the decision-making efficiency can beimproved. When dealing with novice problems for which the user does not have a clear ideaabout what to do, the system can provide the user with some clues or hints to remind him toconsider all of the relevant factors, which will result ina more informed decision. In this sense,the effectiveness of the decision would also be improved. From the problem solving style ormethodology perspective, the model proposed in this thesis is different from the traditional DSapproach. Taking the framework proposed by Sprague and Carison (1982) asa representativeof the traditional decision support systems (DSS) models, a traditional DSS would typicallyprovide a user with decision-making tools, quantitative models, or flexible interfaces. RECOSis based on commitment theory [Becker 60, Gerson 76, Johnso 73] and applies artificialintelligence techniques (e.g., case-based reasoning). It aims at supporting user reasoning.Furthermore, some support provided by RECOS is not typical of traditional DSS, such as:•Alerting the user when he makes a commitment that conflicts with prior commitments;• Suggesting individuals with whom the user can ask to work jointly on the request;• Considering sentimental attributes;32•Conducting simple, single-issue negotiation with the requester or other collaborators;• Automatically processing standard requests;• Providing limited learning capability (i.e., through case base) in handling non-standardrequests;The case-based reasoning emerged from artificial intelligence. Commitment consistency andsentiment consideration are typical features of commitment theory. As we understand it, agentsinteraction and negotiation are not covered by traditional DSSs either.33Chapter 5RECOS Model and Reasoned Action TheoryA commitment mainly concernsa future action. The objective of RECOS is to establish acomputer-based model for supporting a user to act rationally. From this perspective, RECOSis very much related to the Reasoned Action theorydeveloped in social psychology.5.1. A Reasoned Action TheoryReasoned Action (R-A) Theory studies the relationships betweena person’s attitude and intentionto a behaviour and the actual conducting of the behaviour. A well recognized R-A model isdeveloped by Fishbein and Ajzen (75). Tn this model,a behaviourial intention is defined as aperson’s subjective probability to perform the behaviour, and is dependent ontwo factors: apersonal or “attitudinal” factor and a social or “normative” factor. Since there areno otherintervening factors specified between the behaviourintention and behaviour itself, a behaviouris actually determined by the attitude and subjective norm.The attitude to a behaviour is definedas a person’s general feeling of favour or disfavour towardthe behaviour (i.e., the expected behaviour consequencesand the evaluation of theseconsequences). It can be represented by the following formula:(bo*ej).Here, bo1 is an expected outcome, i, from performing the behaviour,ande1 is the evaluation of the outcome, i.The normative factor is called Subjective Norm(SM) since it is perceived by the person himself.Subjective Norm represents the person’s perception that related others think he should or shouldnot perform the behaviour. It can be describedby the following formula:34*m).Here, bn3 is the person’s belief about whether the related referent,j, thinks he shouldperform the behaviour, andrn, is the motivation to comply with the referentj.The model based on the R-A theory can be illustrated by the diagram shown in Figure 2.5.2. An Innovation Adoption Model Based on Reasoned Action TheoryThe R-A theory has been used in the information systems domainto study innovation adoptionbehaviour [Moore 88]. In Moore’s Innovation Adoption Model, innovation is represented byPersonal Work-Station (PWS). The dependent variable is PWSadoption behaviour, which ismeasured in three dimensions: a) adoption action, b) the use of the PWS to a novel domain orto solve a novel problem, and c) the degree to which the innovation is put to use. Independentvariables are the individual’s attitude to the adoption, subjective norm,and the voluntariness ofthe agent to the adoption. Conceptually, attitudeand subjective norm are the same as in the R-Atheory. Voluntariness is defined as the degree to which theuse of PWS is perceived as beingvoluntary, or of free will. Attitude is measured by evaluating and summing the PerceivedCharacteristics of the Innovation (PCI). The PCIs covered in the model are relative advantage,image, avoidance, ease of use, observability, compatibility, and trialability. The referents usedto measure subjective norm are co-workers (peers), immediate superiors, senior management,and subordinates.35--IISSubjectiveNorm+_______BehaviouraBehaviourIntentionBelievedOutcome1*0)EvaluationAAttitudeJtowards_______________ItheBehaviour./——BelievedOutcomen*EvaluationFigure2.AReasonedActionModel(AdoptedfromFishbein&Ajzen,1975)The basic meanings of PCIs used in this model are the following1:- -Relative advantage: the degree to which using an innovation is perceived as being betterthan using its precursor.Image: the degree to which the use of innovation is perceived to enhanceone’simage or status in one’s social system.Compatibifity: the degree to which use of an innovation is perceived as beingconsistent with the existing values, past experiences and needs ofpotential adopters.Ease of use: the degree of difficulty perceivedabout learning to use and actuallyusing an innovation.Observabifity: the degree to which the results of using an innovation are perceived asbeing visible and communicable to others.Trialabifity: the degree to which an individual feels he may try out an innovation ona limited basis before adopting it.Avoidance: the degree that the user wants to avoid the innovationbecause of thenegative effect of its usage.The study was conducted using a survey method, and highlycorrelated relationships were foundbetween the dependent variable and independent variables. Regardingthe relationship betweenthe independent variables, subjective norm and voluntarinessalso affect an agent’s attitude tothe adoption. This model can be described by thediagram of Figure 3.‘All of the PCI definitions are directly adopted from [Moore 88], except for the Trialability, which is adaptedaccording to its meaning used in [Moore 88].37SubjectiveVoluntannessNormRelativeAdvantaeAtitudeImageTowardsInnovationAdoptionAdoptionCompatibilitEaseofrialabilityObservab-AvoidanceFigure3.AnInnovationAdoptationModel(AdaptedfromMoore,1987)5.3. Relation of the RECOS Model and Reasoned Action TheoryWe believe that the RECOS model fits the reasoned action framework well. Accordingto ourdefinition, committing to certain action is equivalent to performing the action in the future.Inthis sense, a commitment is comparable to the “behaviour” (i.e., performing the action)in thereasoned action theory. In RECOS, it is implied that a commitment is primarily afunction ofthe relevant factor evaluation results. The direct resource gains/losses for carrying out therequested action, and the commitment connection effects, if any, would determinethe agent’sattitude to the behaviour. The inter-agent relationship and others’ expectationswould explainthe subjective norm on a decision about the requested action. In this sense,RECOS can belooked at as an application of the R-A theory in handling Request-Commitment problems.Comparing RECOS and Moore’s innovation adoption model, we found that the RECOS modelis more general, but still compatible with Moore’s model. The attitudinaldeterminants inMoore’s model can be classified into two categories. One is directly related to thebenefits forthe adoption, including relative advantage, image, avoidance; the other, including easeof use,observability, compatibility, and trialability, would contribute to determining therequirementsor the difficulty level to successfully implement the adoption, which will affect theoutcomes ofthe adoption. These two types of factors are covered in RECOS, but in a more generalterm(i.e., direct gains/losses). The subjective norm in Moore’smodel is directly borrowed from theR-A theory which has been discussed in the previous paragraph.We agree with Moore that, in addition to behaviour intention (i.e., attitude and subjectivenorm),other factors could also affect an agent’s behaviour. Such a factor presented in Moore’smodelis voluntariness of the agent to adopt the technology. In RECOS, two such factorsare included:organizational regulations and the agent’s competence to fulfil thecommitment. Organizationalregulations are equivalent to voluntariness in Moore’s model. The competence factoris notexplicitly mentioned in Moore’s model, nor in the R-A model discussed above. Webelieve thatthese factors are important in addition to an individual’s intention in determininghis behaviour.No matter how strong an agent’s intention is to a behaviour, the actual conductingof the39behaviour would be moderated by organizational regulations, especially bythe agent’scompetence to fulfil the commitment. On the other hand, competenceand organizationalregulations could also affect an agent’s attitude and thus intention to abehaviour.From the above analysis, we see that RECOS models fit the Reasoned Actiontheory, and arecompatible with another model established on a formal empirical study.The comparisonsbetween RECOS, a Reasoned Action model, and an Innovation Adoptionmodel based on R-Atheory are shown in table 2. On the other hand, the commitment literature,as presented inchapters 3 and 4, provides more useful information and theory for developingRECOS40A Reasoned RECOS AnInnovation AdoptionAction ModelModelRelative AdvantagesImageDirect Gains/Losses AvoidanceAttitude (bo,*e) Commitment Connections CompatibilityEase of UseObservabilityTrialabilitySubject Inter-agent Relationship (bn*m)Norms (bn3*m) Others’ ExpectationsOther CompetenceFactors Regulations VoluntarinessNotes: 1. bo1 is an expected outcome, i, from performing the behaviour.2. e1 is the evaluation to the outcome i.3. bn is the person’s belief about whether the related referent, j, thinks he should perform the behaviour.4. is the motivation to comply with the referent j.Table 2. Comparisons of RECOS Model, A Reasoned Action Model, andan Innovation Adoption Model41Chapter 6Applications of the RECOS ModelIn chapter 4, we have proposed the RECOS model for supporting an agent’s reasoningprocessin handling request-commitment problems. In this chapter we present a sample application usingthe model and a use evaluation, to illustrate the model’s potential usage and to testitslimitations.6.1 A Sample Application Using the ModelIn this section we show a sample to illustrate a possible use and some features of the modelproposed in Chapter 4. Since a complicated example would be too long and difficult to follow,we have deliberately chosen a simple scenario to demonstrate some features of the model.6.1.1 A Brief Description of the ExampleThe system representing the newly-appointed Vice President (VP) in charge of R&D at a largemanufacturing firm, Ron Steward, receives a request to sit on a committee to inspect the acidrain situation in the region. This requires a time commitment of the whole week of October 12to October 16, 1992. The details of the request are as follows:Requester: Environmental Protection SocietyRequest Topic: Sitting on the Acid Rain Inspection CommitteeRequirements:Time: October 12 to October 16, 1992Skills: Knowledge about acid rain.However, the VP is very busy. In particular, he has forgotten that he has a prior commitmenton behalf of his company to visit an overseas research laboratory during the same period oftime. Now, the system tries to assist Ron in coping with this request using its reasoningframework and the knowledge in its knowledge bases.42Very good credibility.Close and important.Participating in external R&D related activities is partof the duty of VP R&D.Resources base:Time: October 12 to October 16, 1992 has been allocated to another activitySkill: Knowledgable in acid rain issueCommitment base: Visiting an overseas research lab from October 10 to October 20, 1992.Now, the system tries to evaluate various factors regarding whether or not the agent shouldcommit to the request. As mentioned in section 4.3.3, the factor evaluation sequence of thereasoning process is not fixed. For the purpose of this example, we describe the reasoningprocess according to the sequence shown in Figure 1.1. Consulting the “agent base”, the system knows that the requester has very good credibility.As the VP R&D in this company, his relationship with this society is close and important.2. The system, by checking with the “organizational knowledge base”, finds that participatingin such an activity is consistent with company regulations.3. For the commitment consistency assessment, the system does not find any directconnection between the request and other commitments.4. By analyzing the request, the agent knows that the primary requirements for committingto such a request would be skill and time. Based on this information, the system evaluatesthe resources available to him. His time for that period is already scheduled. By checkingwith the “commitment base”, the system discovers that the time conflict is with acommitment to visit an overseas research lab. It also determines from consulting the“resource base” that he is knowledgable about acid rain research, a requirement of therequest.5. The system does not know the detailed direct resource gains/losses related to committing6.1.2 Knowledge in the System and the Reasoning ProcessSome relevant knowledge is available in the system’s various knowledge bases:Agent base:The Requester:Relationship with the requester:Organizational knowledge bases:43to or rejecting the request. However, it reminds the user to consider this factor bypresenting this issue to him.After the factor evaluation, the system integrates the results and presents a recommendation toits user.6.1.3 A Sample DialogueIn the following, we offer a sample dialogue between the system (Sys) and the user (Ron) duringthe reasoning process. This dialogue is simplified to highlight the major points.As we mentioned in the previous section, the system has evaluated other factors but needs theuser’s input for the direct gains/losses related to committing to or rejecting the request.1. The system presents a number of options for the direct gains/losses factor:1. Tangible resource gains/losses for committing2. Intangible resource gains/losses for committing3. Tangible resource gains/losses for not committing4. Intangible resource gains/losses for not committing5. Others direct gains/losses not covered by 1-46. ExitRon chooses 1, 2, 4.442. Because Ron chooses “tangible resource gains/losses for committing”, the system presentsthe following options:1. Money2. Time3. Space4. Material5. Skill6. Others7. ExitRon chooses ‘Skill’.Sys: What type of skill would you gain/lose if you commit to the request?Ron: Gain knowledge of current situation of acid rain problem in this region.3. After finishing the “tangible resource gains/losses for committing” evaluation, the systempresents the following options for another choice made by Ron, “intangible resourcegains/losses for committing”:1. Reputation2. Respect3. Loyalty4. Esteem5. Guilt6. Honour7. Others8. ExitRon chooses ‘Reputation’ and ‘Honour’.Sys: How would the commitment to the request affect your reputation?1. Very positive; 2. Positive; 3. No difference; 4. Negative; 5 Very negative.Ron: 1.Since the system interprets that Ron feels it is an honour to sit on the committee, it does not askany questions about this choice.454. Then, the system responds to Ron’s last choice, “intangible gains/losses for notcommitting”, with the following options:1. Reputation2. Respect3. Loyalty4. Esteem5. Guilt6. Others7. ExitRon chooses ‘Reputation’ and ‘Guilt’.Sys: How would it affect your reputation if you do not commit to the request?1. Very positive; 2. Positive; 3. No difference; 4. Negative; 5 Very negative.Ron: 4.Since the system interprets that Ron feels guilty for not committing, it does not ask any questionabout this choice.After the factor evaluation, the system tries to integrate the evaluation results and to propose arecommendation to Ron.Sys: Based on the knowledge I have and the information you gave me, the evaluation resultregarding sitting on the Acid Rain Inspection Committee is as follows:Requester: Environmental Protection Society;Requester Credibility: Very good;Relation with the requester: Close and important;Commitment and Regulation: Consistent;Commitment Consistency: No direct connection detected with other commitments;46Competence:Time: No, youhave a commitmentto visit an overseasresearch laboratoryduring October 10 toOctober 20, 1992.Skills: Yes.If you commit,Tangible Gains:Knowledge of currentsituation of acidrain problemin this region.Tangible Losses:One week of time(The system automaticallytakes the tangibleresource requirementas an investment);Intangible Gains:Very positive effecton your reputation;It is an honour to siton this committee.If you do not commit,Intangible Losses: Negativeeffect to your reputation;You would feelguilty.The evaluation resultsare in favour of committingto the request exceptfor the time conflictwith your visit to the overseasresearch laboratory.I am not clear aboutthe consequencesif younegotiate with the labto change the dateof your visit. Do youthink it is worthwhiletoreschedule your visitin order to commit to thecurrent request?Ron: Yes.Sys: I suggestyou change your visit toNovember 2 - November12, the earliesttime duringwhich you do not have anyimportant commitments.What do youthink?Ron: November2 - November 10.Sys: Do you wantme to negotiate foryou?Ron: Yes.Sys: The negotiationis successful. The laboratoryagrees to yournew agenda.Please give me yourdecision on the requestfrom the EnvironmentalProtection Society.Ron: Commit.Finally, the systemwill record this casein its “case base” forlater usage.476.1.4 DiscussionFrom this simple example we can note several features of a system built on the RECOS model.1. It supports the user by automatically processing part of the reasoning process, using theknowledge in its knowledge bases. This could improve the user’s efficiency andeffectiveness in generating a response. For example, Ron may not know the requester wellsince he is new to this position, but the system, by providing such information, would savehim time, and could possibly help him avoid a mistake if the factor is important inhandling the request.2. It reminds the user about conflicting commitments. Although this point appears as ascheduling problem in the example, it also applies to other types of resources.3. It prompts which factors to evaluate, and also proposes possible factor attributes toconsider. In the example, this is typically shown in the direct gains/losses assessment.Although the terms used in the example are general in nature (e.g., space, material, skill,etc.), they may still have some usefulness in reminding the user to structure his thinking.If an application system were designed for handling specific domain problems, this wouldbe much clearer.4. It presents to the user the pros and cons of committing or not committing. For example,if the user is not competent, the reasons are presented to him.5. It proposes negotiation terms in certain situations.6.2 User EvaluationThe RECOS model is based on research results from different research areas. It requires furthertesting to determine whether the factors considered in the model’s reasoning framework arerelevant in handling real life problems, and also to determine the model’s limitations.Attempting to explore the answers to these questions, we conducted a user evaluation. The basicpurpose of the user evaluation was to learn: 1) the relevance of the factors covered in RECOSto the reasoning process of individuals in handling request-commitment problems; 2) theweaknesses and limitations of the model. We asked users to use the model to handle a real liferequest-commitment problem, and then we solicited their comments about the model.486.2.1 The Design of the Prototype forthe EvaluationTo fulfil the evaluation objectives, we wanted to representthe model in a more structured formatrather than a general description. However,by showing an implemented prototype of the model,we feel that the user might be distracted by the implementationdetails and not focus on theconceptual part. Given this consideration, we developeda set of questions for each of the factorcategories covered by RECOS. Our intention was that, through these questions, the user wouldget a good idea about the model. Most of the questions were not intended for the user’spreciseanswer, but for reminding them about the issuesto think about when they made a decision abouta request. The evaluation objective mightbe fulfilled by presenting the subjects questions onpaper. However, the paper based questions are sequentialin nature and the subjects basicallyneed to go through every question from the beginningto the end. In that case, the subjectswould not see the structure that the RECOS model provides.Furthermore, the subjects may alsoget lost or confused, since some questions are exclusivelogically and not all factors are relevantto certain domain problems. Therefore, we need to present the questions ina more flexible andstructured way to accurately represent the model.Based on this consideration, we coded thequestions into a computerized package which provides: 1) better structure, i.e., the factorsarepresented by menus which mimic the model structure;2) better flexibility in selecting factors,i.e., the user can select any number of factors to evaluateand can go back and forth betweendifferent factor evaluation modules; 3) smoother logic flow, i.e., onlythe necessary questionsare presented to the user according to his/her choice.After developing the first prototype, we did a preliminarytest. The basic purpose of this test wasto get users’ comments on the prototype design and the match between the questions and thefactors they were assumed to represent. At this stage, we had four graduate students try theprototype. All of them have taken at least one empiricalstudy course. Two of them haveundertaken empirical studies by themselves. We foundthis step was useful and constructive.Many suggestions were proposed on the question formatand wording, the match between thequestions and the factors they represented, and user interfaces. Based on these suggestions, theprototype was modified. Some examplesof the prototype screens are shown in Figures 4 - 7.In each of the menus, there is an “Other” option offeredfor the user to probe any factors or49issues which are not covered by the menu options. When the userfinishes the evaluation in thecurrent menu or enters a wrong menu, he/she may quit the current menuimmediately bychoosing “Exit”.Request-Commitment Support SystemThe system is able to assist you in evaluatingany of thefollowing factors which might be relevantfor a decision onthe request.1. Requester, Relationship, andExpectations2. Regulations3. Competence4. Commitment Consistency5. Direct Gains/Losses6. Others7. Help8. ExitMake any number of selections using the RETURNand Arrowkeys. When all selections have been made, pressFiG.Figure 4. The main menu of the evaluationprototypeRequest-Commitment Support SystemRequester, Relationship, and Others’ ExpectationsAmong the following related agents, who wouldcare about yourdecision on the request?1. Family members2. Employer3. Friends4. Colleagues5. Others6. Help7. ExitMake any number of selections using theRETURN and Arrowkeys. When all selections have been made,press FlO.Figure 5. The others’ expectations of the evaluationprototype50Request-Commitment Support SystemCompetencePlease select factors which you think are relevant for adecision on the request.1. Tangible resources requirement to yourself2. Tangible resources requirement to related others3. Intangible resources requirement to yourself4. Intangible resources requirement to related others5. Other requirement not covered by above options6. Help7. ExitMake any number of selections using the RETURN and Arrowkeys. When all selections have been made, press FlO.Figure 6. The competence assessment of the evaluation prototypeRequest-Commitment Support SystemCompetencePlease select the tangible resource type(s) which arerequired from you if you commit.1. Money2. Time3. Space4. Material5. Skill6. Others7. Help8. ExitMake any number of selections using the RETURN and Arrowkeys. When all selections have been made, press FlO.Figure 7. The tangible resource requirement ofthe evaluation prototype516.2.2 The Subjects and the ScenariosThe subjects were two current M.Sc. students, two research associates, one MBA graduate, andone Ph.D. student. Since this is not a formal empirical study, they were not randomly chosen.To evaluate the model, a scenario of request-commitment problems was needed. The request-commitment problem we chose for the user evaluation was “a person you have been datingproposes to marry you.” The reason we have chosen this scenario is that: 1) It is a real lifeproblem that some adults will face, or have faced; 2) It is a relatively complicated problemrequiring some serious thinking to make a decision; and probably reasoning assistance is needed;3) It might demonstrate major features of the RECOS model. This scenario was onlypreparedas the backup and the subjects were encouraged to use their own examples to try themodel. Itturned out that no subject chose to use this example. The reason might be that it is not realisticfor some of our subjects because they are already married or else do not have a boy/girl friend,or it is too personal and sensitive a scenario.The examples used by the subjects for the evaluation were: a request from a real estate agentto make an offer for a particular house, a request from a friend to proofread a big researchpaper, a job offer from a company, a request from a friend for some semi-confidentialinformation about my organization, and a request from a friend to participate in a church activitygroup. Among these examples, “a job offer from a company” was used by two subjects.Although some of the examples were rather simple, they happened in real life, and they didrequire some evaluation and reasoning according to our subjects. Another advantage for usingthese real life scenarios is that the subjects had already thought about them, and thus, it wouldbe easier for them to pin point any weaknesses in the model.6.2.3 The Conduct of the EvaluationThe study was conducted on different days and the subjects attended a tri2l session one by one.At least one day before the study, the subjects were asked to think about a request-commitmentproblem they had encountered, particularly one for which there was no clear answer. At thebeginning of the study, the author briefly introduced the model and the purpose of the study.During the study, the subjects operated the prototype and the author sat beside them to answer52questions and make notes. Discussions occurred during and after the trial. Each sessiontookabout one to one and half hours, depending on the length of the discussion.6.2.4 DiscussionMany recommendations resulted from the study. The Feedback can be classifiedinto twocategories: 1) recognition, and 2) challenges and questions.1. Recognition1) All subjects recognized that the factors covered by the model are relevantto theirreasoning for a commitment, although they found that the weight of each factor might bedifferent, and not all the factors were relevant to every scenario.2) Four of the subjects remarked that a system built on the RECOS model would be usefulin helping people to make better justified and more consistent commitments if the domainknowledge was built in. One subject pointed out that a system built on the model wouldalso be useful in training users to reason rationally and structurally. The systemwouldfamiliarize them with the reasoning framework, and they would continue touse themodel’s framework. Two of them commented that, even at this stage, it already has someprompting capability. Since the usefulness of the model was not a major objective of thisstudy, we did not pursue which factors were prompted by the model but not consideredby the subjects. Another reason that this type of information was not clearlyrevealedmight be that most of the pros and cons about the example had been well considered bythe subjects before they came to the evaluation. Without providing the detailed domainknowledge, the model might not be able to give them much more insight about the request.2. Challenges and QuestionsSince the major purpose of the study was to find out the model’s weaknesses and limitations,a lot of discussions focused on this aspect of the model. The major pointsare summarizedbelow:1) Alternatives and potential commitments. One subject gave the followingscenario:53“Someday a real estate agent may come to me and show me a nice house with a reasonableprice. However, I might still want to look around to check other houses. Can the RECOSmodel help me to evaluate the alternatives and give me a comparison between them?” Healso thought about another issue: “I am planning to buy a house in Vancouver. However,there may be a chance that someday an attractive job offer comes from Toronto. If Icommit to buying the house now, it might conflict with my future commitment for the job.Can the model take this issue into account?”We agree that RECOS may have limitations when it comes to evaluating alternatives orpotentially related commitments. However, in real life, many request-commitment problemsdo not have a foreseeable alternative or a related future commitment, or they are not worthconsidering. For example, in the scenario of “proof-read a big research paper” used byanother subject, there may not be any alternatives (e.g., committing to review another paperfrom someone else) other than “commit”, “reject”, or “negotiate”. There may not be anypotentially related commitments to think about either, because such a commitment can befulfilled in a couple of days, and there is no other request-commitment problem expected.However, in real life, we do encounter a lot of request-commitment problems which involvealternatives and potential commitments. Thus, we must be aware of this issue when applyingthe RECOS model.2) Moral principle and self image. Some subjects pointed out that morale principle and selfimage would also affect one’s decision on a request. We agree, and the RECOS modelhas actually taken these effects into account (i.e., in sentiment). Whether a commitmentis consistent or not with the agent’s moral principle will directly influence his sentiments,either positively or negatively. For example, if one does something against his/her moralprinciples, he/she might feel guilty, shamed, or embarrassed. Otherwise, the effect of themoral principle would not be a relevant factor in the decision. Similarly, the effects of selfimage can also be represented by sentiment. The example used by a subject, “proof-reada big research paper”, illustrates this point. The subject claimed that he “has a goodmastering of written English.” If he rejected the request, it would be inconsistent with his54self-image, putting other factors aside. We explain that the effect, if any, of such aninconsistency between his self-image and behaviour would actually reflect on his feelingabout his self esteem and other related sentiment attributes.3) Resources classification. In RECOS, we classify resources into tangible and intangible(see section 4.2.1) categories. One subject pointed out that skills may not necessarily betangible since not every skill can be measured. Another subject considers only physicalmatters tangible. We agree that such a classification might not be consistent betweensubjects. Such a classification was based on the following definition of “tangible”:“substantially real; conceived or thought of as definable or measurable.” [Gove 67]. Fromthis definition, some components included in skills, such as equipment, are real. Othercomponents, such as knowledge, are also testable or measurable in some sense (e.g., knowor do not know, have or do not have, etc.). On the other hand, sentiments are mostlysubjective matters, which are based on one’s feeling. Thus, sentiments are called intangibleresources and others are called tangible resources. Nevertheless, this classification wasjust for the purpose of convenience. Its precise definition may need further study, but isbeyond the scope of this thesis.4) Domain specific knowledge and personal preferences. One subject pointed out, “whenevaluating a request, I always consider some specific issues about the request. Forexample, when I evaluate a house, in addition to other issues, I also think about itslocations and the safety of the area where the house is located.” This implies that forevaluating a request, domain knowledge is necessary. The RECOS model is a domainindependent reasoning framework, and there is no domain knowledge directly representedat the current stage. However, when an application system is developed, the factorscovered in the model will be adapted to fit the domain. For example, in the real estatedomain, space might be defined as location, the size of the property, the number of roomsin the house, and the size of each room; in the money category, not only the price of thehouse will be included, but also the extra cost for the security supplies and service mightbe considered; and the feelings of secure or insecure will be represented in sentiment.55Nevertheless, some domain specific issues or user specific preferences might notbe fullyrepresented by the factor categories covered in the model. But,at the integration stage,the system will apply the user predefined decisionrules to the factor evaluation results toproduce a recommendation. If something isspecified in a decision rule, but not reflectedin the factor evaluation results, it willbe highlighted and presented to the user for furtherprobing.5) There were some other comments generated in the evaluation, suchas: 1) it is too generala framework without focusing on any domain, 2) a system built on RECOS wouldbe toobig and inefficient, and 3) tools for integratingthe factor evaluation results should bedeveloped. We agree that these issues deservefurther attention. However, the investigationof these issues is beyond the scope of this thesis.56Chapter 7PrototypingTo test the model’s practicality, we have implemented a prototype based onthe RECOS usingTurbo-Prolog [Borlan 88a, 88b, 88cJ. In the remainder of this chapterwe will report: 1) theobjective of the prototyping, 2) the major features implementedin the prototype, and 3) theexperience we have learned from this implementation.7.1 Objective of the PrototypingThe basic objective of the prototyping was: 1) to show what a system built on theRECOS modellooks like, and, in particular, how the system uses its past experience to assistthe user inhandling the current request; how the system uses knowledge availablein its knowledge basesto assist the user to evaluate the relevant factors; and how the systeminteracts with the user tosolicit the required information and present the evaluation result to theuser; 2) to evaluate somepotential problems and difficulties with implementing the model.Based on this objective andthe RECOS model framework, the prototype will neither look intothe detailed knowledge basestructures nor include any integration tools to synthesize the individualfactor evaluation results.What will be presented to the user at the final stage (Integrationin Figure 1) are the resultsobtained from the individual factor evaluations, including theinput from the user.7.2 The Prototype Structure and FeaturesThe structure of the prototype is presented in Figure 8. The function of eachcomponent issimilar to what was discussed in section 4.3. Therefore, we will notrepeat it here. What we willpresent in this section are its major features. The prototype we have implemented isbasicallyan extended version of the one that has been used for the user evaluation.The major featuresof this prototype are: 1) flexible user interfaces; 2) “case base” application; 3)certain factorevaluation automation; 4) evaluation result report.5701SystemhaspreviousCase(Therequestcouldbefromdifferentagent)Figure8.ThePrototypeStructure1. Flexible User InterfacesIn this prototype, we maintained the user interface style used for the userevaluation, butincluded preprocessing, and integration. As the user interfaces in the factor evaluation stagearesimilar to that described in section 6.2.1, here, we mainly show the interfacesin thepreprocessing and integration stages. Figures 9 - 13 are some samples of the userinterfacescreens. The prototype assumes that it receives a request from another agent throughthecomputer network. If there are no previous cases or predefined response for such a request,itgives the user four options to choose from: 1) Making a decision right away,2) viewing therequest information, 3) using the system to do the evaluation, or 4) handlingthe requestmanually (Figure 9). If the system has previous experience (i.e., cases) in handling similarrequests, it will present the user with another set of options (Figure 10). When the systemsolicits knowledge about certain factors, it will show the user some possible options, and alsoleave the user flexibility to use his own scale (Figure 11). In this way, the user retainsthemaximum possible flexibility and controls the reasoning process.2. “Case Base” ApplicationA major feature of this prototype is using its past experience to aid the user inhandling thecurrent request-commitment problem. Figure 10 shows that if the system has experienceindealing with a similar request, it will present the user with the decision in the previous case,andwill also allow him to review the case information. The system assists the user with two typesof cases. First, the system will try to find a case with the same request topic andthe samerequester as the current one. If this trial fails, it will retrieve the case with the same topic butfrom a different agent. We believe this manner of case screening would give the userthe mostrelevant and closest past experience possible. On the other hand, the reasoning processforreaching a decision is also a knowledge acquisition process for the system. It will store the finalevaluation result as a new case for future applications. When the system first encounters arequest from a new agent, it will most likely need to solicit most of the informationfrom theuser. When it meets the same request from the same agent, or a different request fromthe sameagent, or the same request from a different agent, it will be able to release theuser fromevaluating certain factors, such as agent credibility, inter-agent relationship,and regulations.59In this sense, the prototype possesses limited learning capability. Wewould like to point outthat the use of cases in this prototype is a very simple application ofthe case-based techniquedeveloped in artificial intelligence [Hammon 89, Kolodn 88]. If amore sophisticated case-basedreasoning mechanism is used, the system would be more useful.3. Certain Factors Evaluation AutomationUnder certain situations, the prototype can assess certain factors (e.g.,requester credibility,inter-agent relationship) on its own, without interrupting the user.This is done by applying theavailable knowledge in its knowledge bases. This feature’s application and usefulnesshave beendiscussed in sections 6.1.2 and 6.1.4. Thus, we will not repeat that descriptionin this section.4. Evaluation ReportAfter the individual factor evaluation, the system will present the overallevaluation results tothe user for his judgement (Figure 12). This conforms well with one of the suggestionsfrom theuser evaluation, discussed in section 6.2, which was to show the factor evaluationresult to theuser at the integration stage. After the user reviews the result, the systemwill show anotherscreen to solicit the user’s decision (Figure 13).Dear user, welcome to the Commitment Reasoning Support System.You have a request from Dr. Gorden King. It is ‘giving a seminar about commitments’.Please choose one of the following options to proceed in handling therequest:1. Making a decision right away2. Viewing the detailed request information3. Starting the factor evaluation4. Handling the request manuallyMake your selection by pressing the RETURN key.Figure 9. A preprocessing menu when the system has noexperience60Dear user, welcome to the Commitment Reasoning Support System.You have a request from John Smith. It is about ‘go to dinner’. According to aprevious case, you committed to a similar request from Ken Lee. I checked yourresources, and found you have the resources to fulfil the requirements ofthe request.Please choose one of the following options to proceed in handling the request:1. Making a decision right away2. Reviewing the case information3. Viewing the detailed information of current request4. Going on the evaluation5. Handling the request manuallyMake your selection by pressing the RETURN key.Figure 10. A Preprocessing menu when the system has experienceI do not have the information about your relationship with Dr. Gorden King. Pleasedefine your relationships with this agent by choosing one of the options:1. Important2. Not important3. Not clear4. Self defined termMake your selection by pressing the RETURN key.Figure 11. Acquiring information on inter-agent relationship61Based on the information I have, I believe you have the skill and time to fulfil therequirements of the request, giving a seminar about commitments, from Dr. GordenKing. However, other factor evaluations should also be considered before making yourdecision, which are shown below:The credibility of the requester: Very good;Your relationship with the requester: Close and Important;Relation to Regulations: Consistent;Relation to other commitments: No direct connection;Competence: Yes;If you commit,The direct gains: A free dinner;One day free sight seeing of Vancouver;Positive effect to your reputation;Positive effect to your respect;The direct losses: Two days of time;If you do not commit,The direct gains: none;The direct losses: Feel guilty;Negative effect on others’ respect for you.Press any RETURN to continue to the next step.Figure 12. A factor evaluation result report62After reviewing the factor evaluation results about the request, giving a seminar aboutcommitments, from Dr. Gorden King, you might be ready to make a decision now.Please choose one of the following options to proceed in handling the request:1. Committing to the request2. Rejecting the request3. Negotiating with the requester4. OthersMake your selections by Pressing the RETURN key.Figure 13. A menu after showing the evaluation result7.3 DiscussionFrom the prototype implementation we learned the following.Case-based reasoning mechanism might be a major tool for implementing RECOS. Anagent acts in an organizational environment, which is an open system [Gasser 91, Hewitt911.From the prototyping, it is clearer to the author that it is impossible and not feasibleto capture complete knowledge in the system (e.g., we cannot exhaustively capture allregulations). However, through the case-based technique, the system can collect the mostrelevant information into the system. If a similar request repeatedly occurs, then the systemwould be able to provide more and more support to the user. Eventually, the user mayonly need to pay the minimum attention to handling certain requests, and let the systemdo the job for him.2. Separating the domain knowledge from the reasoning mechanism.To fulfil the objective of the prototyping, a major issue was to carry the evaluation resultsfrom one stage to the next. At the beginning, we tried to use clause parameters (a clause inProlog is similar to procedure call in other languages) to carry the information. However,when recursion (the central reasoning mechanism of the prototype) and application informationpassing combined together, the system behaviour became difficult to control. Later on, we63took the advantage of the database facility in Turbo-Prolog and used databases as a mediumto pass the information from one stage to another. In this way, the reasoning mechanism wasreleased from transferring data, the prototype was structured better, and the system behaviourwas under control. We believe that the separation of the reasoning mechanism and theapplication information transferring has a general implication for implementing the RECOSmodel for domain applications.64Chapter 8ConclusionWe have presented RECOS, a computer-based model for supporting an agent’s reasoningprocessin dealing with request-commitment problems in a cooperative multi-agents environment. Toconclude the thesis, we will discuss the thesis’ contributions, its limitations, and future researchdirections in this chapter.8.1 ContributionsThe major contribution of this thesis is that it collects a set of domain-independent factors fromdifferent areas related to making commitments (e.g., commitment research in sociology [Becker60, Gerson 76, and Johnso 73] and DAT [Gasser 91, Hewitt 91], a social rule system theory[BurFia 87], and a contract theory [Macnei 80]), it proposes a reasoning framework for applyingthese factors, and it presents a computer-based model to support an individual’s reasoningprocess for making a commitment (particularly, in selecting and evaluating the relevant factors).People in artificial intelligence and information systems research have tried to usethecommitment concept to model organizational activities and to support cooperative work in amulti-agent environment. However, little has been done to support an individual’s reasoningprocess in making a commitment, and it is on this which the RECOS model focuses. Its majorusefulness lies in its general reasoning framework, on which the domain application systems canbe based. A prototype has been developed for the model. It is simple and preliminary, but wedid learn something from the prototyping process, which can be useful for developing applicationsystems in the future.RECOS is not another model for decision-making which generates the best reward for the agent.It emphasizes a commitment’s effects on both the committed individual and the communityinwhich the individual is acting (e.g., by reminding the user to be aware of others’ expectations,organizational regulations, and sentiments). This consideration is important because anindividual’s well-being and an organization’s well-being are closely related [Gerson 76]. This65feature distinguishes the RECOS model from most other traditional decision support models.The second contribution of this work is its insight into the model obtained from a userevaluation. Although the user evaluation was very simple in nature, it did reveal a number ofthe model’s weaknesses and limitations, its potential uses, and issues that should be addressedregarding the model’s application and implementation.The third contribution is the classification of commitment connections. In commitment research,the linkage between commitments is highly emphasized. Resource sharing has been taken as themedium for such links [Gerson 76, Gasser 91, Hewitt 91]. In this thesis, it is noted that, inaddition to resource sharing, commitments can be linked through other mediums (e.g.,commitments themselves). In this thesis this type of linkage of commitments is called directconnection, while resource sharing is called indirect connection. The direct connection may alsoresult in gains/losses in resources but the resource is not the medium for such a connection. Forexample, accepting ajob offer from another company may result in losing part of one’s pensionplan in the current company. However, it is not the resource, but the terms defined in thepension plan, which he has committed, directly connecting the pension plan with the commitmentto the company. Separating the resource sharing and the direct commitment connection mightprovide better insight into resolving commitment conflicts.8.2 Limitations and Research DirectionsWe believe that RECOS is useful for an individual to make better justified and more consistentcommitments in a cooperative multi-agent environment. However, as have other models, it alsohas some limitations which should be considered when the model is applied.As revealed in the user evaluation, the RECOS model may not be well-suited to deal withrequest-commitment problems which have alternatives or potential future commitments. Thisissue should be taken into consideration when applying RECOS to solve real life problems.However, we believe that this problem could be resolved by designing a higher level control66mechanism, which calls RECOS to evaluate each of the alternatives,and manages thecomparisons of the evaluation results of the alternatives.In section 4.2.7, we have discussed that there are potential overlaps between thefactorcategories. This implies that the user might consider one factor in two or more categories(e.g.,reconsidering others’ expectations in sentiment evaluation). However, we believe that there aremore benefits than drawbacks in separating these factors. As longas the user is aware of thispotential problem, its negative effect willbe minimized or eliminated. This should beunderstood in order to maximize the usage of this model.The RECOS model only provides support in selecting factorsto consider and in evaluating suchfactors for making a commitment. The assistance provided for integrationis very limited. Assome subjects pointed out during the model evaluation session,a set of integration tools is highlyrecommended. We agree that this is an important direction for futurestudy.RECOS is a domain-independent model, and many componentsare treated as “black boxes” atthe current stage. Its real usefulness can only be judged through application systems, whichcanbe used in real life commitment-making. To build application systems, the internal structure ofthe “black boxes” needs to be represented, and some factors(e.g., sentiment attributes) needto be measured. We foresee that much needs to be done in this direction in order to appreciatethe model’s full benefits. In addition, to build an applicationsystem, the developer not onlyneeds the model but also a set of powerful tools with whichto work. Some existing languages(e.g., Prolog) might be used for this purpose, but more suitable and user-friendly tools aredesirable.67References[A1HrA1 73] Alutto, J., Hrebiniak, L., Alonso, R., “On Operationalizing the Concept ofCommitment,” Social Force, Vol. 51, No. 4, June, 1973, 448-454[BarOuc 86] Barney, J. B. and Ouchi, W. G. (eds.), Organizational Economics, JosseyBass, San Francisco, 1986[Becker 60] Becker, H. S., “Notes of the Concept of Commitment,” The American Journalof Sociology, Vol. 66, No. 1, July 1960, 32-40[BhaCro 90] Bhandaru, N. and Croft, W.B., “An Architecture for Supporting Goal-BasedCooperative Work,” in Multi-User Inteifaces and Applications, Gibbs, S and Verrijn-Stuart,A.A., (eds.), Elsevier Science Publishers B.V. North-Holland, 1990, 337-354[Bond 90] Bond, A. H., “Commitment: A computational model for organizations of cooperatingintelligent agents,” Proceedings of Conference of Office Information Systems, Cambridge,Massachusetts, April, 25-27, 1990, 21-30[Borlan 88a] Borland International, Turbo Prolog: User’s Guide, Scotts Valley, CA., USA, 1988[Borlan 88b] Borland International, Turbo Prolog: Reference Guide, Scotts Valley, CA., USA,1988[Borlan 88c] Borland International, Turbo Prolog: ToolBox, Scotts Valley, CA., USA, 1988[Brickm 87] Brickman, P., Commitment, Conflict, and Caring, Prentice-Hall, Inc. EnglewoodCliffs, New Jersey, 1987[Bunge 77] Bunge, M., Treatise on Basic Philosophy: Vol. 3, Ontology I: The Furniture of theWorld, Reidel, Boston, 1977[Bunge 79] Bunge, M., Treatise on Basic Philosophy: Vol. 4, Ontology II: A World of Systems,Reidel, Boston, 1977[BurFia 87] Burns, T. R., and Flam, H., The Shaping of Social Organization: Social RuleSystem Theory with Application, SAGE Publications, London, 198768[ChaWoo 91] Chang, M. K., Woo, C. C. “SANP: A Communication Level ProtocolforNegotiations,” Decentralized Al3 (Proceedings of the Third European Workshop onModelling Autonomous Agents in a Multi Agent World, Kaiserslautern, Germany, August 5-7,1991), edited by Y. Demazeau and E. Werner, Netherlands: ElsevierScience PublishersB.V., 1992, to appear.[CohLev 90] Cohen, P.R., and Levesque H., Intention is Choice with Commitment,”Artificial Intelligence, Vol. 42, 1990, 213-261[DeKlee 86] De Klee, J., “An Assumption-Based TMS,” Artificial Intelligence,Vol. 28, 1986,127-162[Doyle 79] Doyle, J., “A truth maintenance System,” Artificial intelligence, Vol.12, 1979,495-516[Fikes 81] Fikes, R. E. “A Commitment-Based Framework for Describing Informal CooperativeWork,” Proceedings of the Third Annual Conferenceof the Cognitive Science Society,Berkeley, California, August 19-21, 1981, 17-22[FisAjz 75] Fishbein, M., and Ajzen, I., BELIEF, ATTITUDE, INTENTION AND BEHAVIOR.an Introduction to Theory and Research, Addison-Wesley Publishing Company, 1975[F1GrHW881Flores, F., Graves, M., Hartfield, B., Winograd, T., “Computer Systems andthe Design of Organizational Interaction,” ACM Transaction on Office Information Systems,Vol. 6, No. 2, April, 1988, 153-172[FloLud 80] Flores, F., Ludlow, J. J., “Doing and Speaking in the Office,” in DecisionSupport Systems Issues and Challenges G.Fick and R.H. Sprague (eds.), 1980, 95-118,[Gasser 91] Gasser, L., “Social conceptions of knowledgeand action: DAT foundations andopen systems semantics,” Artificial Intelligence, Vol. 47, 1991, 107-138[GenNil 87] Genesereth, M. R., and Nilson, N. J., Logical FoundationsofArtjficialIntelligence, Morgan Kaufman, Los Altos, California, 1987[Gerard 68] Gerard, H.B., “Basic Features of Commitment,” in Theoriesof CognitiveConsistency A source Book, Abelson, R.P., et al. (eds), Rand McNally and Company,Chicago, 1968[Gerson 76] Gerson B. M., “On ‘quality of life’,” American Sociology Review, Vol. 41,October, 1976, 793-806[Gove 67] Gove, P.B. (ed.), Webster’s Third New World Dictionary of the English LanguageUnabridged, G&C Merrian Company Publishers, Springfield, Massachusetts, USA, 196769[HaJaRo 90] Hahn, U., Jarke, M., and Rose, T.,“Group Work in Software Projects:Integrated Conceptual Models and CollaborationTools,” in Multi-User Interfaces andApplications, Gibbs, S and Verrijn-Stuart, A.A.,(eds.), Elsevier Science Publishers B.V.,North-Holland, 1990, 83-101[Hammon 89] Hammond, K. (ed.), Proceedingsof Case-Based Reasoning Workshop, PensacolaBeach, FL, 1989[Hewitt 91] Hewitt, C., “Open Information SystemsSemantics for Distributed ArtificialIntelligence,” Artificial Intelligence,Vol. 47, 1991, 79-106[JanMan 77] Janis, I., Mann, L., DecisionMaking, A Psychological Analysis of Conflict,Choice, and Commitment, The Free Press, New York, 1977[Johnso 73] Johnson, M. P., “Commitment: A ConceptualStructure and Empirical Application,”Sociological Quarterly, Vol, 14, No.3, Summer, 1973, 395-406[Kiesle 71] Kiesler, C.A., The Psychologyof Commitment Experiments Linking Behaviourto Belief, Academic Press, New Yorkand London, 1971[Kolodn 88] Kolodner, J.L. (ed.),Proceedings ofthe 1988 Workshop on Case-Based Reasoning,Morgan Kaufmann, San Mateo, CA,1988[Konoli 85] Konolige, K. “A Computational Theoryof Belief Introspection”. IJCAI 1985,Vol. 1, Los Angeles, California, 502-508,[Koo 88] Koo, C. C., “A Commitment-based CommunicationModel for Distributed OfficeEnvironments,” Proceeding of the Conferenceon Office Information Systems, Palo Alto,California, March 23-25, 1988, 291-298[McArth 88] McArthur, G. L., “Reasoning aboutknowledge and belief: a survey”.Computational Intelligence, Vol. 4, No.3, August, 1988, 223-243[Macnei 80] Macneil, I.R., The NewSocial Contract, An Inquiry into Modem contractualRelations, Yale University Press, New Haven and London, 1980[MaGLRR 87] Malone, T. W., Grant, K. R., Lai,K. Y, Rao, R, and Rosenblitt, D.,“Semistructured Messages Are Surprisingly Useful for Computer-Supported Coordination,”ACM Transactions on Office Information Systems, Vol.5, No. 2, April 1987, 115-131[Masloh 89] Mason, C. L. and Johnson, R. R., “DATMS:A Framework for distributedAssumption Based Reasoning,” Distributed Artificial Intelligence,Vol.2, Gasser, L., Huhns,M. N. 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G.,Negotiation Behaviour, Academic Press, Inc., 1981, New York[[Sayeed 89] Sayeed, Omer-Bin, “Perception of OrganizationalCommitment: PreliminaryFindings and Scale Construction,” Indian Journal of Social Work, Vol.50, No. 3, July, 1989,317-328[Simon 57] Simon, H.A., Administrative Behaviour:A Study ofDecision-Making Processes inAdministrative Organization, The Macmillan Company, New York,1977[SprCar 82] Sprague, R. H. Jr. and Carison,E. D., Building Effective Decision SupportSystems, Prentice-Hall, Inc., Englewood Cliffs,N.J., USA, 1982[V0KaDL 90] VoB, A., Karbach, W., Drouven,U., Lorek, D., “Competence Assessment inConfiguration Tasks,” Ai Communications,Vol. 3, No. 3, Sept, 1990, 107-114[WanWoo 91] Wand, Y., and Woo,C. C., “An Approach to Formalizing OrganizationalOpen Systems Concepts,” Proceedings of the (ACM& IEEE) Conference on OrganizationalComputing Systems, Atlanta, Georgia, November5-8, 1991, 141-14671AppendixThis appendix includes figures describing the detailed structure of the reasoning componentscontained in Figure 1. In all these figures, the meaning of each symbol is as follows: an ovalrepresents a process in which factor evaluation or other reasoning is done;a vertical rectanglerepresents the user or another agent; a vertical rectangle with corners rounded represents aknowledge base; an arrow between ovals or between an oval and a box depicts the workingdirection, with the information flowing from the starting oval/box to the end one; an arrowbetween an oval and a knowledge base means that the process retrieves a specified item fromthe knowledge base; and a double arrow means there are some information exchangesbetweenthe involved parties.72TopicFigure Al: The reasoning process of the “Preprocessing Module“in Figure 1.CaseBaseProduce ResponseMove on to Factor Evaluation73Figure A2. The reasoning process of the “Requester,Inter-agent relationship, and Other’s Expectations” in Figure 174Figure A3: The reasoning process of Regu1ation Assessment” in Figure1.Organizational.4KnowledgBase75Figure A4: The reasoning process of “Commitment Consistence”in Figure 1.miImentLBaseDirectconnectionDirect CommitmentConnection Check76Figure A5: The reasoning process of” Competence Assessment” in Figure 1.RequirementsAssessmentrCaseLBase77Figure A6: The reasoning process of “Direct Gains/Losses”in Figure 1.4GsoeN,ssnLç2IncomingRequestInformationCase BaseCheckCannot78


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