326 search results - page 17 / 66 » Reinforcement Learning Based on On-Line EM Algorithm |
ICMLA
2008
14 years 11 months ago
2008
In reinforcement learning, it is a common practice to map the state(-action) space to a different one using basis functions. This transformation aims to represent the input data i...
PKDD
2010
Springer
14 years 8 months ago
2010
Springer
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
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AAAI
1996
14 years 11 months ago
1996
Procedural representations of control policies have two advantages when facing the scale-up problem in learning tasks. First they are implicit, with potential for inductive genera...
GECCO
2006
Springer
15 years 1 months ago
2006
Springer
Two mathematical and two computational theories from the field of human and animal learning are combined to produce a more general theory of adaptive behavior. The cornerstone of ...
EUROCAST
2007
Springer
15 years 4 months ago
2007
Springer
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...