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» Abstracting Reusable Cases from Reinforcement Learning
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ICCBR
2005
Springer
15 years 2 months ago
Abstracting Reusable Cases from Reinforcement Learning
Andreas von Hessling, Ashok K. Goel
ECAI
2010
Springer
14 years 10 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
15 years 1 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
15 years 2 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