118 search results - page 5 / 24 » An Evolutionary Random Policy Search Algorithm for Solving M... |
GECCO
2005
Springer
14 years 28 days 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...
JAIR
2008
13 years 7 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...
ATAL
2007
Springer
14 years 1 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...
ICML
2008
IEEE
14 years 8 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...
CORR
2012
Springer
12 years 3 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 ...