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» Abstracting Reusable Cases from Reinforcement Learning
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ICCBR
2005
Springer
13 years 10 months ago
Abstracting Reusable Cases from Reinforcement Learning
Andreas von Hessling, Ashok K. Goel
ECAI
2010
Springer
13 years 5 months ago
Case-Based Multiagent Reinforcement Learning: Cases as Heuristics for Selection of Actions
This work presents a new approach that allows the use of cases in a case base as heuristics to speed up Multiagent Reinforcement Learning algorithms, combining Case-Based Reasoning...
Reinaldo A. C. Bianchi, Ramon López de M&aa...
EWCBR
2006
Springer
13 years 8 months ago
Multi-agent Case-Based Reasoning for Cooperative Reinforcement Learners
Abstract. In both research fields, Case-Based Reasoning and Reinforcement Learning, the system under consideration gains its expertise from experience. Utilizing this fundamental c...
Thomas Gabel, Martin Riedmiller
EVOW
2003
Springer
13 years 10 months ago
Exploring the T-Maze: Evolving Learning-Like Robot Behaviors Using CTRNNs
Abstract. This paper explores the capabilities of continuous time recurrent neural networks (CTRNNs) to display reinforcement learning-like abilities on a set of T-Maze and double ...
Jesper Blynel, Dario Floreano