Enhancing multi-agent based simulation with human-like decision making strategies
MABS 2000 Proceedings of the second international workshop on Multi-agent based simulation
Extending the recognition-primed decision model to support human-agent collaboration
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
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Artificial Intelligence
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AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Information supply chain: a unified framework for information-sharing
ISI'05 Proceedings of the 2005 IEEE international conference on Intelligence and Security Informatics
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One of the challenging issues in a distributed time sensitive information rich environment is how to assist the decision makers to make decisions quickly and effectively. This paper describes a decision model that has been developed for such situations and how using the RCAST agent architecture can assist the humans in dealing with the information challenges. The example demonstrates how the system can be used in a military scenario.