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Approximation Techniques in Multiagent Learning

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Abstraction, Reformulation, and Approximation (SARA 2002)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2371))

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Abstract

Research in multiagent systems includes the investigation of algorithms that select actions for multiple agents coexisting in the same environment. Multiagent systems are becoming increasingly relevant within artificial intelligence, as software and robotic agents become more prevalent. Robotic soccer, disaster mitigation and rescue, automated driving, and information and e-commerce agents are examples of challenging multiagent domains. As the automation trend continues, we need robust algorithms for coordinating multiple agents, and for effectively responding to other external agents.

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Relevant Publications

  1. Michael Bowling and Manuela Veloso. Bounding the suboptimality of reusing subproblems. In Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, pages 1340–1345, Stockholm, Sweden, August 1999. Morgan Kaufman.

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  2. Michael Bowling and Manuela Veloso. Multiagent learning using a variable learning rate. Artificial Intelligence, 2002. In Press.

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  3. Michael Bowling and Manuela M. Veloso. Existence of multiagent equilibria with limited agents. Technical report CMU-CS-02-104, Computer Science Department, Carnegie Mellon University, 2002.

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  4. [Bowling et al. 2002]_Michael Bowling, Rune Jensen, and Manuela Veloso. A formalization of equilibria for multiagent planning. In AAAI Workshop on Planning with and for Multiagent Systems, Edmonton, Canada, July 2002. To Appear.

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© 2002 Springer-Verlag Berlin Heidelberg

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Bowling, M. (2002). Approximation Techniques in Multiagent Learning. In: Koenig, S., Holte, R.C. (eds) Abstraction, Reformulation, and Approximation. SARA 2002. Lecture Notes in Computer Science(), vol 2371. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45622-8_28

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  • DOI: https://doi.org/10.1007/3-540-45622-8_28

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43941-7

  • Online ISBN: 978-3-540-45622-3

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