Learning policies through argumentation-derived evidence
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Information systems in modeling interactive computations on granules
Theoretical Computer Science
Argumentation strategies for plan resourcing
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
Prognostic normative reasoning in coalition planning
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
Recognizing team context during simulated missions
Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work
Introduction to prognostic normative reasoning
AAMAS'11 Proceedings of the 10th international conference on Advanced Agent Technology
On the benefits of argumentation-derived evidence in learning policies
ArgMAS'10 Proceedings of the 7th international conference on Argumentation in Multi-Agent Systems
Exploiting domain knowledge in making delegation decisions
ADMI'11 Proceedings of the 7th international conference on Agents and Data Mining Interaction
An agent architecture for prognostic reasoning assistance
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Learning strategies for task delegation in norm-governed environments
Autonomous Agents and Multi-Agent Systems
Interactive information systems: Toward perception based computing
Theoretical Computer Science
Argumentation strategies for collaborative plan resourcing
ArgMAS'11 Proceedings of the 8th international conference on Argumentation in Multi-Agent Systems
Argumentation strategies for task delegation
EUMAS'11 Proceedings of the 9th European conference on Multi-Agent Systems
Prognostic normative reasoning
Engineering Applications of Artificial Intelligence
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In this paper, we describe how agents can support collaborative planning within international coalitions, formed in an ad hoc fashion as a response to military and humanitarian crises. As these coalitions are formed rapidly and without much lead time or co-training, human planners may be required to observe a plethora of policies that direct their planning effort. In a series of experiments, we show how agents can support human planners, ease their cognitive burden by giving advice on the correct use of policies and catch possible violations. The experiments show that agents can effectively prevent policy violations with no significant extra cost.