92 search results - page 8 / 19 » Acting Optimally in Partially Observable Stochastic Domains |
ECML
2005
Springer
15 years 3 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...
AIPS
2008
14 years 12 months ago
2008
We consider the problem of cooperative multiagent planning under uncertainty, formalized as a decentralized partially observable Markov decision process (Dec-POMDP). Unfortunately...
TR
2010
14 years 4 months ago
2010
Abstract--We examine optimal repair strategies for wind turbines operated under stochastic weather conditions. In-situ sensors installed at wind turbines produce useful information...
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AAAI
2004
14 years 11 months ago
2004
The search for finite-state controllers for partially observable Markov decision processes (POMDPs) is often based on approaches like gradient ascent, attractive because of their ...
ICRA
2010
IEEE
14 years 8 months ago
2010
IEEE
Abstract— We propose a planning algorithm that allows usersupplied domain knowledge to be exploited in the synthesis of information feedback policies for systems modeled as parti...