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Annual Conference of ITA ACITA 2009 Agent Support for Policy-driven Collaborative Planning in Ad-hoc Teams Martin J. Kollingbaum, Timothy J. Norman Computing.

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Presentation on theme: "Annual Conference of ITA ACITA 2009 Agent Support for Policy-driven Collaborative Planning in Ad-hoc Teams Martin J. Kollingbaum, Timothy J. Norman Computing."— Presentation transcript:

1 Annual Conference of ITA ACITA 2009 Agent Support for Policy-driven Collaborative Planning in Ad-hoc Teams Martin J. Kollingbaum, Timothy J. Norman Computing Science, University of Aberdeen, UK Communication Interface Planning Interface Communication Interface Planning Interface Humanitarian Party Military Party Agent Critic/Censor Agent Critic/Censor Intelligence Request for Support Commitments Plan Quality: - Rescue wounded as early as possible - Minimize norm violations Plan Quality: - Minimize cost of military action and support to humanitarian party - Minimize norm violations Humanitarian Organisation Has to evacuate wounded from regions where a military task force is operating. Collaboration with military force is essential to guarantee the safety of the humanitarian operation Challenges for agent support: (a)mission policies have to be represented in a form that can be processed by a software agent (b)such an agent must be able to keep track of the ``normative state'' of the human planner -- what are the planner's current obligations, permissions and prohibitions, and (c)the agent must be able to reason about the current actions of the human planner, so that it can provide feedback about violations of policies, and advise the human planner about alternative courses of action. Human test subjects use a planning and communication environment to create plans and communicate in a controlled language. Agents are tested in two designs: 1.Critic condition: the agent detects policy violations of human planners. The agent (a) intercepts the sending of a message or (b) interrupts the planning of actions due to violating actions -- the planner can then decide whether to adhere to such an advice 2.Censor condition: the agent still monitors the activities of the human planner, but silently interferes with the communication by deleting offending parts of the exchanged messages Prohibition of Humanitarian Organisation (Party A): -IF you have intelligence of threats along route R on day D AND you do not have a commitment of escort from party B for route R on day D THEN you are forbidden from deploying ground and air vehicles along route R on day D Prohibition of Humanitarian Organisation (Party A): -IF you have intelligence of threats along route R on day D AND you do not have a commitment of escort from party B for route R on day D THEN you are forbidden from deploying ground and air vehicles along route R on day D Katia Sycara, Jean Oh, Joseph A. Giampapa Robotics Institute, Carnegie Mellon University, USA Scenario Prohibition of Military Force (Party B): -IF you grant clearance to party A for route R on day D OR you commit to escort party B along route R on day D THEN you are prohibited from performing military operations along route R on day D Prohibition of Military Force (Party B): -IF you grant clearance to party A for route R on day D OR you commit to escort party B along route R on day D THEN you are prohibited from performing military operations along route R on day D Military Force Has to perform military operations against insurgent strongholds. Collaboration with humanitarian organisation is essential to guarantee save evacuation of wounded. The creation of joint plans within teams is a complex task: (a)Teams are formed ad-hoc with limited co-training, (b)For joint missions, each team member has to form a (sub-)plan, the sum of all sub-plans forms the overall joint plan (c)Each team member holds private mission policies, planning constraints and has to plan under these policies and constraints without knowing the plans of other team members (d)Information exchange between team members has to take place to guarantee the consistency of the overall joint plan. (e)The overall joint plan may not be known in its completeness to any of the team members. ProblemAgent Support Experiments References: Martin J Kollingbaum, Joseph A. Giampapa, Katia Sycara, Timothy J. Norman (2009). Agent Support for Collaborative Mission Planning in Ad-hoc Teams. ACITA Chris Burnett, Daniele Masato, Mairi McCallum, Timothy J. Norman, Joseph A. Giampapa, Martin J. Kollingbaum, Katia Sycara (2008). Agent Support for Mission Planning under Policy Constraints. ACITA Wamberto Vasconcelos, Martin J. Kollingbaum, Timothy J. Norman (2007). Resolving Conflict and Inconsistency in Norm- regulated Virtual Organizations. AAMAS 2007


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