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AAAI
2006
13 years 9 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
SARA
2007
Springer
14 years 1 months ago
Active Learning of Dynamic Bayesian Networks in Markov Decision Processes
Several recent techniques for solving Markov decision processes use dynamic Bayesian networks to compactly represent tasks. The dynamic Bayesian network representation may not be g...
Anders Jonsson, Andrew G. Barto
ECML
2005
Springer
14 years 1 months ago
Active Learning in Partially Observable Markov Decision Processes
This paper examines the problem of finding an optimal policy for a Partially Observable Markov Decision Process (POMDP) when the model is not known or is only poorly specified. W...
Robin Jaulmes, Joelle Pineau, Doina Precup
NIPS
2004
13 years 9 months ago
Coarticulation in Markov Decision Processes
We investigate an approach for simultaneously committing to multiple activities, each modeled as a temporally extended action in a semi-Markov decision process (SMDP). For each ac...
Khashayar Rohanimanesh, Robert Platt Jr., Sridhar ...
AIPS
2004
13 years 9 months ago
Heuristic Refinements of Approximate Linear Programming for Factored Continuous-State Markov Decision Processes
Approximate linear programming (ALP) offers a promising framework for solving large factored Markov decision processes (MDPs) with both discrete and continuous states. Successful ...
Branislav Kveton, Milos Hauskrecht