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» Reinforcement learning
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204
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ILP
2007
Springer
15 years 8 months ago
Building Relational World Models for Reinforcement Learning
Abstract. Many reinforcement learning domains are highly relational. While traditional temporal-difference methods can be applied to these domains, they are limited in their capaci...
Trevor Walker, Lisa Torrey, Jude W. Shavlik, Richa...
107
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AUSAI
2004
Springer
15 years 8 months ago
A Dynamic Allocation Method of Basis Functions in Reinforcement Learning
In this paper, we propose a dynamic allocation method of basis functions, an Allocation/Elimination Gaussian Softmax Basis Function Network (AE-GSBFN), that is used in reinforcemen...
Shingo Iida, Kiyotake Kuwayama, Masayoshi Kanoh, S...
125
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ECML
2004
Springer
15 years 8 months ago
Analyzing Multi-agent Reinforcement Learning Using Evolutionary Dynamics
In this paper, we show how the dynamics of Q-learning can be visualized and analyzed from a perspective of Evolutionary Dynamics (ED). More specifically, we show how ED can be use...
Pieter Jan't Hoen, Karl Tuyls
AGENTS
2001
Springer
15 years 7 months ago
A social reinforcement learning agent
We report on the use of reinforcement learning with Cobot, a software agent residing in the wellknown online community LambdaMOO. Our initial work on Cobot (Isbell et al.2000) pro...
Charles Lee Isbell Jr., Christian R. Shelton, Mich...
113
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IJCAI
2007
15 years 4 months ago
Utile Distinctions for Relational Reinforcement Learning
We introduce an approach to autonomously creating state space abstractions for an online reinforcement learning agent using a relational representation. Our approach uses a tree-b...
William Dabney, Amy McGovern