1235 search results - page 103 / 247 » Reinforcement learning in a nutshell |
AAAI
1998
15 years 7 days ago
1998
In this paper, we describe methods for e ciently computing better solutions to control problems in continuous state spaces. We provide algorithms that exploit online search to boo...
ICANN
2010
Springer
14 years 12 months ago
2010
Springer
We propose a new approach for reinforcement learning in problems with continuous actions. Actions are sampled by means of a diffusion tree, which generates samples in the continuou...
101
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GECON
2008
Springer
14 years 12 months ago
2008
Springer
The application of autonomous agents by the provisioning and usage of computational resources is an attractive research field. Various methods and technologies in the area of arti...
96
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NN
2006
Springer
14 years 10 months ago
2006
Springer
We discuss an important property called the asymptotic equipartition property on empirical sequences in reinforcement learning. This states that the typical set of empirical seque...
92
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PKDD
2010
Springer
14 years 9 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...