118 search results - page 5 / 24 » An Evolutionary Random Policy Search Algorithm for Solving M... |
111
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GECCO
2005
Springer
15 years 9 months ago
2005
Springer
Recent adaptive image interpretation systems can reach optimal performance for a given domain via machine learning, without human intervention. The policies are learned over an ex...
124
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JAIR
2008
15 years 3 months ago
2008
Partially Observable Markov Decision Processes (POMDPs) provide a rich framework for sequential decision-making under uncertainty in stochastic domains. However, solving a POMDP i...
131
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ATAL
2007
Springer
15 years 9 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...
105
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ICML
2008
IEEE
16 years 4 months ago
2008
IEEE
In apprenticeship learning, the goal is to learn a policy in a Markov decision process that is at least as good as a policy demonstrated by an expert. The difficulty arises in tha...
151
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CORR
2012
Springer
13 years 11 months ago
2012
Springer
Abstract— In this paper, we consider a class of continuoustime, continuous-space stochastic optimal control problems. Building upon recent advances in Markov chain approximation ...