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ISAAC
2010
Springer
13 years 5 months ago
2010
Springer
Howard's policy iteration algorithm is one of the most widely used algorithms for finding optimal policies for controlling Markov Decision Processes (MDPs). When applied to we...
IJCAI
2003
13 years 9 months ago
2003
Markov decision processes (MDPs) and contingency planning (CP) are two widely used approaches to planning under uncertainty. MDPs are attractive because the model is extremely gen...
PKDD
2010
Springer
13 years 5 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...
GECCO
2005
Springer
14 years 1 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...
IJCAI
2003
13 years 9 months ago
2003
The problem of deriving joint policies for a group of agents that maximize some joint reward function can be modeled as a decentralized partially observable Markov decision proces...