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Carnegie Mellon Robotics Institute

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Abstract

Adaptation in open, multi-agent information gathering systems is important for several reasons. These reasons include the inability to accurately predict future problem-solving work-loads, future changes in existing information requests, future failures and additions of agents and data supply resources, and other future task environment characteristic changes that require system reorganization. We are developing a multi-agent financial portfolio management system that must deal with all of these problems. This paper will briefly describe our approaches and solutions at several different levels within the agents: adaptation at the organizational, planning, scheduling, and execution levels. We discuss our solution for execution-level adaptation in detail, and present empirical evidence backing up the theory behind the solution.

Notes

Text Reference

Katia Sycara, K. Decker, and M. Williamson, "Intelligent Adaptive Information Agents," AAAI-96 workshop "Intelligent Adaptive Agents", August, 1996.

BibTeX Reference

@inproceedings{Sycara_1996_2177,
   author = "Katia Sycara and K. Decker and M. Williamson",
   title = "Intelligent Adaptive Information Agents",
   booktitle = "AAAI-96 workshop "Intelligent Adaptive Agents"",
   month = "August",
   year = "1996",
}

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