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Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 2
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Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 3
Dynamic Evaluation of Coordination Mechanisms for Autonomous Agents
EPIA '01 Proceedings of the10th Portuguese Conference on Artificial Intelligence on Progress in Artificial Intelligence, Knowledge Extraction, Multi-agent Systems, Logic Programming and Constraint Solving
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Learning when and how to coordinate
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Reasoning about commitments in multiple concurrent negotiations
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Managing commitments in multiple concurrent negotiations
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AIKED'10 Proceedings of the 9th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases
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ESAW'04 Proceedings of the 5th international conference on Engineering Societies in the Agents World
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This paper develops and evaluates a new decision theoretic framework in which autonomous agents can make rational choices about coordinating their actions. The framework covers the decisions that are involved in determining when and how to coordinate, when to respond to requests for coordination and when it is profitable to drop contracts in order to exploit better opportunities. Our motivating hypothesis is that enabling agents to dynamically set and re-assess both their degree of commitment to one another and the sanctions for decommitment according to their prevailing circumstances will make coordination more effective. This hypothesis is evaluated, empirically, in a grid-world scenario, taking into account three levels of commitments (total, partial and loose) and three kinds of sanctions (fixed, partially sanctioned and sunk cost).