771 search results - page 42 / 155 » Markov Decision Processes with Arbitrary Reward Processes |
112
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NIPS
2001
15 years 3 months ago
2001
Policy gradient methods for reinforcement learning avoid some of the undesirable properties of the value function approaches, such as policy degradation (Baxter and Bartlett, 2001...
190
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ILP
2007
Springer
15 years 8 months ago
2007
Springer
Abstract. Many reinforcement learning domains are highly relational. While traditional temporal-difference methods can be applied to these domains, they are limited in their capaci...
139
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NIPS
2007
15 years 3 months ago
2007
Bayesian Reinforcement Learning has generated substantial interest recently, as it provides an elegant solution to the exploration-exploitation trade-off in reinforcement learning...
116
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CORR
2008
Springer
15 years 1 months ago
2008
Springer
We study the problem of dynamic spectrum sensing and access in cognitive radio systems as a partially observed Markov decision process (POMDP). A group of cognitive users cooperati...
110
Voted
JMLR
2006
15 years 1 months ago
2006
We propose a novel approach to optimize Partially Observable Markov Decisions Processes (POMDPs) defined on continuous spaces. To date, most algorithms for model-based POMDPs are ...