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» Compositional Models for Reinforcement Learning
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CG
2000
Springer
14 years 1 days ago
Chess Neighborhoods, Function Combination, and Reinforcement Learning
Abstract. Over the years, various research projects have attempted to develop a chess program that learns to play well given little prior knowledge beyond the rules of the game. Ea...
Robert Levinson, Ryan Weber
JMLR
2010
148views more  JMLR 2010»
13 years 2 months ago
A Generalized Path Integral Control Approach to Reinforcement Learning
With the goal to generate more scalable algorithms with higher efficiency and fewer open parameters, reinforcement learning (RL) has recently moved towards combining classical tec...
Evangelos Theodorou, Jonas Buchli, Stefan Schaal
CEC
2007
IEEE
14 years 2 months ago
Evolving neuromodulatory topologies for reinforcement learning-like problems
— Environments with varying reward contingencies constitute a challenge to many living creatures. In such conditions, animals capable of adaptation and learning derive an advanta...
Andrea Soltoggio, Peter Dürr, Claudio Mattius...
PE
2000
Springer
95views Optimization» more  PE 2000»
13 years 7 months ago
Compositional performance modelling with the TIPPtool
Stochastic process algebras have been proposed as compositional specification formalisms for performance models. In this paper, we describe a tool which aims at realising all bene...
Holger Hermanns, Ulrich Herzog, Ulrich Klehmet, Va...