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ICML
2001
IEEE
14 years 5 months ago
Symmetry in Markov Decision Processes and its Implications for Single Agent and Multiagent Learning
This paper examines the notion of symmetry in Markov decision processes (MDPs). We define symmetry for an MDP and show how it can be exploited for more effective learning in singl...
Martin Zinkevich, Tucker R. Balch
JMLR
2006
116views more  JMLR 2006»
13 years 4 months ago
Point-Based Value Iteration for Continuous POMDPs
We propose a novel approach to optimize Partially Observable Markov Decisions Processes (POMDPs) defined on continuous spaces. To date, most algorithms for model-based POMDPs are ...
Josep M. Porta, Nikos A. Vlassis, Matthijs T. J. S...
ICML
2006
IEEE
14 years 5 months ago
Learning the structure of Factored Markov Decision Processes in reinforcement learning problems
Recent decision-theoric planning algorithms are able to find optimal solutions in large problems, using Factored Markov Decision Processes (fmdps). However, these algorithms need ...
Thomas Degris, Olivier Sigaud, Pierre-Henri Wuille...
AAAI
2006
13 years 6 months ago
An Iterative Algorithm for Solving Constrained Decentralized Markov Decision Processes
Despite the significant progress to extend Markov Decision Processes (MDP) to cooperative multi-agent systems, developing approaches that can deal with realistic problems remains ...
Aurélie Beynier, Abdel-Illah Mouaddib