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Meta-Level Reasoning in Deliberative Agents
Beijing, China September 20-September 24
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/IAT.2004.13429362004 IEEE/WIC/ACM International Confe ...
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Anita Raja, The University of North Carolina at Charlotte
Victor Lesser, University of Massachusetts Amherst
Deliberative agents operating in open environments must make complex real-time decisions on scheduling and coordination of domain activities. These decisions are made in the context of limited resources and uncertainty about the outcomes of activities. We describe a reinforcement learning based approach for efficient meta-level reasoning. Empirical results showing the effectiveness of meta-level reasoning in a complex domain are provided.
Citation:
Anita Raja, Victor Lesser, "Meta-Level Reasoning in Deliberative Agents," iat, pp.141-147, 2004 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT'04), 2004
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