495 search results - page 37 / 99 » Constructing States for Reinforcement Learning |
171
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NN
2007
Springer
15 years 3 months ago
2007
Springer
Reinforcement learning is based on exploration of the environment and receiving reward that indicates which actions taken by the agent are good and which ones are bad. In many app...
148
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ATAL
2007
Springer
15 years 10 months ago
2007
Springer
To cope with large scale, agents are usually organized in a network such that an agent interacts only with its immediate neighbors in the network. Reinforcement learning technique...
115
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AAAI
2000
15 years 5 months ago
2000
We have constructed ADVISOR, a two-agent machine learning architecture for intelligent tutoring systems (ITS). The purpose of this architecture is to centralize the reasoning of a...
109
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ECML
2003
Springer
15 years 9 months ago
2003
Springer
Abstract. Most of multi-agent reinforcement learning algorithms aim to converge to a Nash equilibrium, but a Nash equilibrium does not necessarily mean a desirable result. On the o...
137
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ICCBR
2010
Springer
15 years 8 months ago
2010
Springer
In this paper we present an approach for reducing the memory footprint requirement of temporal difference methods in which the set of states is finite. We use case-based generaliza...