26 search results - page 5 / 6 » An approximate algorithm for solving oracular POMDPs |
176
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ATAL
2007
Springer
16 years 12 days ago
2007
Springer
Distributed Partially Observable Markov Decision Problems (Distributed POMDPs) are a popular approach for modeling multi-agent systems acting in uncertain domains. Given the signi...
149
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ECML
2005
Springer
15 years 11 months ago
2005
Springer
Abstract. Learning to act in an unknown partially observable domain is a difficult variant of the reinforcement learning paradigm. Research in the area has focused on model-free m...
162
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ATAL
2006
Springer
15 years 10 months ago
2006
Springer
Decentralized partially observable Markov decision processes (DEC-POMDPs) form a general framework for planning for groups of cooperating agents that inhabit a stochastic and part...
171
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NIPS
1998
15 years 7 months ago
1998
A simple learning rule is derived, the VAPS algorithm, which can be instantiated to generate a wide range of new reinforcementlearning algorithms. These algorithms solve a number ...
203
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AIPS
2009
15 years 7 months ago
2009
Probabilistic Roadmaps (PRM) are a commonly used class of algorithms for robot navigation tasks where obstacles are present in the environment. We examine the situation where the ...