201 search results - page 27 / 41 » Solving Concurrent Markov Decision Processes |
119
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IJRR
2010
14 years 8 months ago
2010
Partially observable Markov decision processes (POMDPs) provide a principled, general framework for robot motion planning in uncertain and dynamic environments. They have been app...
139
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PKDD
2010
Springer
14 years 7 months ago
2010
Springer
Partially observable Markov decision processes (POMDPs) are widely used for planning under uncertainty. In many applications, the huge size of the POMDP state space makes straightf...
CPAIOR
2008
Springer
14 years 11 months ago
2008
Springer
The one-step anticipatory algorithm (1s-AA) is an online algorithm making decisions under uncertainty by ignoring future non-anticipativity constraints. It makes near-optimal decis...
CDC
2009
IEEE
15 years 2 months ago
2009
IEEE
Abstract— In this paper we consider several problems involving control with limited actuation and sampling rates. Event-based control has emerged as an attractive approach for ad...
AIPS
2009
14 years 11 months ago
2009
When modeling real-world decision-theoretic planning problems in the Markov decision process (MDP) framework, it is often impossible to obtain a completely accurate estimate of tr...