Taming decentralized POMDPs: Towards efficient policy computation for multiagent settings

IJCAI International Joint Conference on Artificial Intelligence

Volumn , Issue , 2003, Pages 705-711

  Nair, R ^a   Tambe, M ^a   Yokoo, M ^b   Pynadath, D ^c   Marsella, S ^c  

^a University of Southern California   (United States)

^b Nippon Telegraph and Telephone Corporation   (Japan)

^c UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPLEXITY ANALYSIS; EMPIRICAL - COMPARISONS; JOINT REWARDS; MULTI-AGENT SETTING; OPTIMAL ALGORITHM; PARTIALLY OBSERVABLE MARKOV DECISION PROCESS; PIECEWISE LINEAR; SEARCH ALGORITHMS;

DYNAMIC PROGRAMMING; MULTI AGENT SYSTEMS; OPTIMIZATION;

ALGORITHMS;

EID: 84880823326     PISSN: 10450823     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (11)

1. D. Bernstein, S. Zilberstein, and N. Immerman. The complexity of decentralized control of MDPs. InUAI, 2000.
2. C. Boutilier. Planning, learning & coordination in multiagent decision processes. In TARK-96, 1996.
3. A. Cassandra, M. Littman, and N. Zhang. Incremental pruning: A simple, fast, exact method for partially observable markov decision processes. In UAI, 1997.
4. I. Chades, B. Scherrer, and F. Charpillet. A heuristic approach for solving decentralized-pomdp: Assessment on the pursuit problem. In SAC, 2002.
5. L. Kaelbling, M. Littman, and A. Cassandra. Planning and acting in partially observable stochastic domains. Artificial Intelligence, 101, 1998.
6. G. Monahan. A survey of partially observable markov decision processes: Theory, models and algorithms. Management Science, 101(1): 1-16, January 1982. (Pubitemid 12523662)
7. C. Papadimitriou and J. Tsitsiklis. Complexity of markov decision processes. Mathematics ofOperatios Research, 12(3):441-450, 1987.
8. L. Peshkin, N. Meuleau, K. E. Kim, and L. Kaelbling. Learning to cooperate via policy search. In UAI, 2000.
9. D. Pynadath and M. Tambe. The communicative multiagent team decision problem: Analyzing teamwork theories and models. JAIR, 2002.
10. Edward J. Sondik. The optimal control of partially observable markov processes. Ph.D. Thesis, Stanford, 1971.
11. P. Xuan, V. Lesser, and S. Zilberstein. Communication decisions in multiagent cooperation. In Agents-01, 2001.