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» Approximate planning for decentralized MDPs with sparse inte...
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ML
2002
ACM
143views Machine Learning» more  ML 2002»
13 years 5 months ago
A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes
An issue that is critical for the application of Markov decision processes MDPs to realistic problems is how the complexity of planning scales with the size of the MDP. In stochas...
Michael J. Kearns, Yishay Mansour, Andrew Y. Ng
ATAL
2005
Springer
13 years 11 months ago
A polynomial algorithm for decentralized Markov decision processes with temporal constraints
One of the difficulties to adapt MDPs for the control of cooperative multi-agent systems, is the complexity issued from Decentralized MDPs. Moreover, existing approaches can not ...
Aurélie Beynier, Abdel-Illah Mouaddib
JAIR
2008
126views more  JAIR 2008»
13 years 5 months ago
Optimal and Approximate Q-value Functions for Decentralized POMDPs
Decision-theoretic planning is a popular approach to sequential decision making problems, because it treats uncertainty in sensing and acting in a principled way. In single-agent ...
Frans A. Oliehoek, Matthijs T. J. Spaan, Nikos A. ...
ATAL
2008
Springer
13 years 7 months ago
Reinforcement learning for DEC-MDPs with changing action sets and partially ordered dependencies
Decentralized Markov decision processes are frequently used to model cooperative multi-agent systems. In this paper, we identify a subclass of general DEC-MDPs that features regul...
Thomas Gabel, Martin A. Riedmiller
ATAL
2007
Springer
13 years 12 months ago
Q-value functions for decentralized POMDPs
Planning in single-agent models like MDPs and POMDPs can be carried out by resorting to Q-value functions: a (near-) optimal Q-value function is computed in a recursive manner by ...
Frans A. Oliehoek, Nikos A. Vlassis