1325 search results - page 35 / 265 » Algorithm Selection using Reinforcement Learning |
124
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ICML
2007
IEEE
16 years 3 months ago
2007
IEEE
Reinforcement learning algorithms can become unstable when combined with linear function approximation. Algorithms that minimize the mean-square Bellman error are guaranteed to co...
132
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IJCNN
2008
IEEE
15 years 8 months ago
2008
IEEE
— When an agent observes its environment, there are two important characteristics of the perceived information. One is the relevance of information and the other is redundancy. T...
130
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DAGM
2007
Springer
15 years 6 months ago
2007
Springer
Abstract. In this article we present EANT2, a method that creates neural networks (NNs) by evolutionary reinforcement learning. The structure of NNs is developed using mutation ope...
126
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ICML
2006
IEEE
16 years 3 months ago
2006
IEEE
Reinforcement learning (RL) was originally proposed as a framework to allow agents to learn in an online fashion as they interact with their environment. Existing RL algorithms co...
102
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ICML
2003
IEEE
16 years 3 months ago
2003
IEEE
Hierarchical reinforcement learning is a general framework which attempts to accelerate policy learning in large domains. On the other hand, policy gradient reinforcement learning...