1325 search results - page 107 / 265 » Algorithm Selection using Reinforcement Learning |
143
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NIPS
2001
15 years 4 months ago
2001
We propose a new approach to reinforcement learning which combines least squares function approximation with policy iteration. Our method is model-free and completely off policy. ...
128
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PRIB
2010
Springer
15 years 1 months ago
2010
Springer
We studied 1372 LacI-family transcription factors and their 4484 DNA binding sites using machine learning algorithms and feature selection techniques. The Naive Bayes classifier a...
129
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AI
2006
Springer
15 years 6 months ago
2006
Springer
Sentence selection shares some but not all the characteristics of Automatic Text Categorization. Therefore some but not all the same techniques should be used. In this paper we stu...
120
Voted
ECML
2007
Springer
15 years 9 months ago
2007
Springer
We present Policy Gradient Actor-Critic (PGAC), a new model-free Reinforcement Learning (RL) method for creating limited-memory stochastic policies for Partially Observable Markov ...
147
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AAMAS
2007
Springer
15 years 9 months ago
2007
Springer
Learning Automata (LA) were recently shown to be valuable tools for designing Multi-Agent Reinforcement Learning algorithms. One of the principal contributions of LA theory is that...