Toward error-bounded algorithms for infinite-horizon DEC-POMDPs

10th International Conference on Autonomous Agents and Multiagent Systems 2011, AAMAS 2011

Volumn 2, Issue , 2011, Pages 889-896

  Dibangoye, Jilles S ^a   Mouaddib, Abdel Illah ^b   Chaib Draa, Brahim ^c  

^a ECOLE DES MINES DE DOUAI   (France)

^b UNIVERSITÉ DE CAEN   (France)

^c UNIVERSITÉ LAVAL   (Canada)

Author keywords

Artificial intelligence; Decentralized pomdps; Point based solvers

Indexed keywords

ARTIFICIAL INTELLIGENCE; AUTONOMOUS AGENTS; BENCHMARKING; MULTI AGENT SYSTEMS;

ALGORITHMIC FRAMEWORK; APPROXIMATE ALGORITHMS; DECENTRALIZED POMDPS; NEAR-OPTIMAL SOLUTIONS; POINT-BASED; STANDARD ALGORITHMS; SUFFICIENT STATISTICS; THEORETICAL GUARANTEES;

ALGORITHMS;

EID: 84899456254     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (18)

1. C. Amato, D. S. Bernstein, and S. Zilberstein. Optimizing memory-bounded controllers for decentralized pomdps. In UAI, 2007.
2. C. Amato, J. S. Dibangoye, and S. Zilberstein. Incremental policy generation for finite-horizon dec-POMDPs. in ICAPS, 2009.
3. R. Aras and A. Dutech. An investigation into Mathematical Programming for Finite Horizon Decentralized POMDPs. in JAIR, 2010. to appear.
4. D. S. Bernstein, C. Amato, E. A. Hansen, and S. Zilberstein. Policy iteration for decentralized control of Markov Decision Processes. JAIR, 34:89-132, 2009.
5. D. S. Bernstein, R. Givan, N. Immerman, and S. Zilberstein. The complexity of decentralized control of Markov Decision Processes. Math. Oper. Res., 27(4), 2002.
6. A. Boularias and B. Chaib-draa. Exact dynamic programming for decentralized POMDPs with lossless policy compression. In ICAPS, pages 20-27, 2008.
7. A. Carlin and S. Zilberstein. Value-based observation compression for DEC-POMDPs. In AAMAS, 2008.
8. J. S. Dibangoye. Contribution à la resolution des problèmes décisionnels de Markov centralisés et décentralisé s: algorithmes et théorie. PhD thesis.
9. J. S. Dibangoye, B. Chaib-draa, and A.-I. Mouaddib. Policy iteration algorithms for DEC-POMDPs with discounted rewards, in MSDM, 2009.
10. J. S. Dibangoye, A.-I. Mouaddib, and B. Chaib-draa. Point-based incremental pruning heuristic for solving finite-horizon DEC-POMDPs. in AAMAS, 2009.
11. E. A. Hansen, D. S. Bernstein, and S. Zilberstein. Dynamic programming for partially observable stochastic games. In AAAI, pages 709-715, 2004.
12. A. Kumar and S. Zilberstein. Point-based backup for decentralized pomdps: complexity and new algorithms. In AAMAS, pages 1315-1322, 2010.
13. M. L. Putterman. Markov Decision Processes: Discrete Stochastic Dynamic-Programming. John Wiley and Sons, New York, NY, 1994.
14. D. V. Pynadath and M. Tambe. Multiagent teamwork: analyzing the optimality and complexity of key theories and models. In AAMAS, pages 873-880, 2002.
15. Z. Rabinovich, C. V. Goldman, and J. S. Rosenschein. The complexity of multiagent systems: the price of silence. In AAMAS, pages 1102-1103, 2003.
16. S. Seuken and S. Zilberstein. Formal models and algorithms for decentralized decision making under uncertainty. JAAMAS, 17(2):190-250, 2008.
17. D. Szer and F. Charpillet. An optimal best-first search algorithm for solving infinite horizon DEC-POMDPs. In ECML, pages 389-399, 2005.
18. D. Szer and F. Charpillet. Point-based dynamic programming for DEC-POMDPs. In AAAI, pages 16-20, July 2006.