Offline planning for communication by exploiting structured interactions in decentralized MDPs

Proceedings - 2009 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2009

Volumn 2, Issue , 2009, Pages 193-200

  Mostafa, Hala ^a   Lesser, Victor ^a  

^a University of Massachusetts Amherst   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

LIMIT PROBLEM; NEW MODEL; OFF-LINE PLANNING; PROBLEM SIZE; PROBLEM STRUCTURE; SOLUTION ALGORITHMS; SOLUTION QUALITY; SOLUTION TIME; SPECIAL STRUCTURE; STRUCTURED MODEL;

COMMUNICATION; INTELLIGENT AGENTS;

PROBLEM SOLVING;

EID: 78650588583     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WI-IAT.2009.150     Document Type: Conference Paper

References (13)

1. M. Allen. Agent Interactions In Decentralized Environments. PhD thesis, University of Massachusetts, Amherst, 2008.
2. M. Allen, M. Petrik, and S. Zilberstein. Interaction structure and dimensionality reduction in decentralized MDPs. In Proceedings of the Twenty-Third National Conference on Artificial Intelligence, Illinois, USA, July 2008.
3. R. Becker, A. Carlin, V. Lesser, and S. Zilberstein. Analyzing Myopic Approaches for Multi-Agent Communication. Computational Intelligence, 25(1):31-50, February 2009.
4. R. Becker, V. Lesser, and S. Zilberstein. Decentralized Markov decision processes with event-driven interactions. In Proceedings of The Third International Joint Conference on Autonomous Agents and Multi Agent Systems, volume 1, pages 302-309, USA, 2004. IEEE Computer Society.
5. R. Becker, S. Zilberstein, V. Lesser, and C. V. Goldman. Solving transition independent decentralized Markov decision processes. Journal of Artificial Intelligence Research, 22:423-455, 2004.
6. D. Bernstein, R. R. Givan, N. Immerman, and S. Zilberstein. The complexity of decentralized control of Markov decision processes. Mathematics of Operations Research, 27(4):819-840, 2002.
7. C. Goldman and S. Zilberstein. Decentralized control of cooperative systems: Categorization and complexity analysis. Journal of Artificial Intelligence Research, 2:143-174, 2004.
8. D. Koller, N. Megiddo, and B. von Stengel. Efficient computation of equilibria for extensive two-person games. Games and Economic Behavior, 14, 1996.
9. R. Nair, M. Tambe, M. Roth, and M. Yokoo. Communication for improving policy computation in distributed POMDPs. In Proceedings of The Third International Joint Conference on Autonomous Agents and Multiagent Systems, pages 1098-1105. ACM Press, 2004.
10. M. Petrik and S. Zilberstein. A bilinear programming approach for multiagent planning. Journal of Artificial Intelligence Research, 35:235-274, 2009.
11. M. Roth, R. Simmons, and M. M. Veloso. Reasoning about joint beliefs for execution-time communication decisions. In Proceedings of The Fourth International Joint Conference on Autonomous Agents and Multi Agent Systems, 2005.
12. M. T. J. Spaan, G. J. Gordon, and N. Vlassis. Decentralized planning under uncertainty for teams of communicating agents. In Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems, pages 249-256. ACM, 2006.
13. P. Xuan and V. Lesser. Multi-agent policies: From centralized ones to decentralized ones. In Proceedings of the First International Joint Conference on Autonomous Agents and Multi Agent Systems, pages 1098-1105. ACM Press, 2002.