1. Annual Conference of ITA ACITA 2009 Agent Assistance in Forming Swift Trust in Ad-Hoc Decision-Making Teams Chris Burnett cburnett@abdn.ac.uk Timothy J. Norman t.j.norman@abdn.ac.uk Katia Sycara katia+@cs.cmu.edu Problem Modern coalition operations frequently require the integration and collaboration of highly diverse forces, often with very limited experience working together Within such ad-hoc teams, members must be able to delegate tasks to, and subsequently rely upon, each other, requiring trust Such teams are characterized by unfamiliarity, diversity, rapid formation and short life-span, all are barriers to trust formation [4] Problem Modern coalition operations frequently require the integration and collaboration of highly diverse forces, often with very limited experience working together Within such ad-hoc teams, members must be able to delegate tasks to, and subsequently rely upon, each other, requiring trust Such teams are characterized by unfamiliarity, diversity, rapid formation and short life-span, all are barriers to trust formation [4] Approach We are interested in how intelligent agents may support this process by automatically collecting and integrating data to support trust evaluations for human decision makers, specifically in ad-hoc team environments Traditional multi-agent trust approaches rely on direct and reputational experiences lacking in ad-hoc team environments Categorical Assumptions and Monitoring can provide evidence to a trust model in the absence of experiential evidence [3] Approach We are interested in how intelligent agents may support this process by automatically collecting and integrating data to support trust evaluations for human decision makers, specifically in ad-hoc team environments Traditional multi-agent trust approaches rely on direct and reputational experiences lacking in ad-hoc team environments Categorical Assumptions and Monitoring can provide evidence to a trust model in the absence of experiential evidence [3] Model Agents require a cognitive model of trust which integrates available evidence to produce trust beliefs [1] (Figure 1) Subjective Logic [2] provides our underlying subjective belief representation When both direct and reputational evidence is insufficient, categorical assumptions and monitoring provide agents with additional evidence These support tentative decisions which provide stronger direct experiences Model Agents require a cognitive model of trust which integrates available evidence to produce trust beliefs [1] (Figure 1) Subjective Logic [2] provides our underlying subjective belief representation When both direct and reputational evidence is insufficient, categorical assumptions and monitoring provide agents with additional evidence These support tentative decisions which provide stronger direct experiences References [1] R. Falcone and C. Castelfranchi. Social trust: a cognitive approach. Trust and Deception in Virtual Societies, pages 55–90, 2001. [2] A. Jøsang, R. Hayward, and S. Pope. Trust network analysis with subjective logic. In Proceedings of the 29th Australasian Computer Science Conference-Volume 48, pages 85–94. Australian Computer Society, Inc. Darlinghurst, Australia, Australia, 2006. [3] D. Meyerson, K. Weick, and R. Kramer. Swift trust and temporary groups. Trust in Organizations: Frontiers of Theory and Research, 195, 1996. [4] R. Pascual, M. Mills, and C. Blendell. Supporting distributed and ad-hoc team interaction. In People In Control: An International Conference on Human Interfaces in Control Rooms, Cockpits and Command Centres, 1999., pages 64–71, 1999 Monitoring Delegation in ad-hoc teams does not rely on trust alone. When trust is insufficient, a mixture of trust and monitoring behaviors is used With monitoring, trust is only required for the elements of a task for which it is lacking However, monitoring will incur costs on both parties in a delegation relationship, hampering effectiveness Monitoring should provide rapid feedback of evidence to the trust model, and be reduced as trust increases Monitoring Delegation in ad-hoc teams does not rely on trust alone. When trust is insufficient, a mixture of trust and monitoring behaviors is used With monitoring, trust is only required for the elements of a task for which it is lacking However, monitoring will incur costs on both parties in a delegation relationship, hampering effectiveness Monitoring should provide rapid feedback of evidence to the trust model, and be reduced as trust increases Categorical Trust Humans deal with lack of evidence by importing categorical information from previous collaborative settings. This is done by stereotyping; generalizing from individuals to types of agents and their trustworthiness. Agents can engage in such behavior by learning relationships between features of collaboration partners and expected performance. This allows for an agent to form a tentative trust evaluation even when there are no direct or reputational evidence sources for a particular candidate Categorical Trust Humans deal with lack of evidence by importing categorical information from previous collaborative settings. This is done by stereotyping; generalizing from individuals to types of agents and their trustworthiness. Agents can engage in such behavior by learning relationships between features of collaboration partners and expected performance. This allows for an agent to form a tentative trust evaluation even when there are no direct or reputational evidence sources for a particular candidate Trust Dimensions Competence – Does the candidate have the ability to undertake task T? Disposition – Will the candidate behave the way I expect? Normative Consistency – can the candidate be trusted to observe norms? Normative Conflict – will the candidate encounter normative conflicts? Conflict Resolution – what are the candidates priorities over norms? These distinctions affect monitoring and intervention strategies Trust Dimensions Competence – Does the candidate have the ability to undertake task T? Disposition – Will the candidate behave the way I expect? Normative Consistency – can the candidate be trusted to observe norms? Normative Conflict – will the candidate encounter normative conflicts? Conflict Resolution – what are the candidates priorities over norms? These distinctions affect monitoring and intervention strategies Monitoring Types Passive Trustor (A) observes trustee (B) No communication required Violations must be inferred from observation alone – costly for A Reactive A requests reports from B at As discretion – B cannot anticipate monitoring requests Proactive B sends reports to A at Bs discretion - A must trust B to honestly and accurately report Scheduled Monitoring communication occurs at predefined intervals Frequency crucial in determining effectiveness Both agents can anticipate monitoring activity Monitoring Types Passive Trustor (A) observes trustee (B) No communication required Violations must be inferred from observation alone – costly for A Reactive A requests reports from B at As discretion – B cannot anticipate monitoring requests Proactive B sends reports to A at Bs discretion - A must trust B to honestly and accurately report Scheduled Monitoring communication occurs at predefined intervals Frequency crucial in determining effectiveness Both agents can anticipate monitoring activity Fig. 2: Monitoring Fig. 1: Trust model overview