495 search results - page 64 / 99 » Constructing States for Reinforcement Learning |
199
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PKDD
2010
Springer
15 years 1 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...
157
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ICML
2001
IEEE
16 years 4 months ago
2001
IEEE
Direct policy search is a practical way to solve reinforcement learning problems involving continuous state and action spaces. The goal becomes finding policy parameters that maxi...
135
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ICCS
1993
Springer
15 years 8 months ago
1993
Springer
Adaptive predictive search (APS), is a learning system framework, which given little initial domain knowledge, increases its decision-making abilities in complex problems domains....
163
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CI
2005
15 years 4 months ago
2005
Autonomous agents that learn about their environment can be divided into two broad classes. One class of existing learners, reinforcement learners, typically employ weak learning ...
140
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CDC
2010
IEEE
14 years 11 months ago
2010
IEEE
Abstract-- We consider reinforcement learning, and in particular, the Q-learning algorithm in large state and action spaces. In order to cope with the size of the spaces, a functio...