26 search results - page 5 / 6 » An approximate algorithm for solving oracular POMDPs |
ATAL
2007
Springer
13 years 11 months 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...
ECML
2005
Springer
13 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...
ATAL
2006
Springer
13 years 9 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...
NIPS
1998
13 years 6 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 ...
AIPS
2009
13 years 6 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 ...