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ICMLA
2003
13 years 9 months ago
A Distributed Reinforcement Learning Approach to Pattern Inference in Go
— This paper shows that the distributed representation found in Learning Vector Quantization (LVQ) enables reinforcement learning methods to cope with a large decision search spa...
Myriam Abramson, Harry Wechsler
GECCO
2004
Springer
155views Optimization» more  GECCO 2004»
14 years 28 days ago
Genetic Network Programming with Reinforcement Learning and Its Performance Evaluation
A new graph-based evolutionary algorithm named “Genetic Network Programming, GNP” has been proposed. GNP represents its solutions as directed graph structures, which can improv...
Shingo Mabu, Kotaro Hirasawa, Jinglu Hu
IWCLS
2007
Springer
14 years 1 months ago
On Lookahead and Latent Learning in Simple LCS
Learning Classifier Systems use evolutionary algorithms to facilitate rule- discovery, where rule fitness is traditionally payoff based and assigned under a sharing scheme. Most c...
Larry Bull
GECCO
2010
Springer
153views Optimization» more  GECCO 2010»
13 years 11 months ago
Multi-task evolutionary shaping without pre-specified representations
Shaping functions can be used in multi-task reinforcement learning (RL) to incorporate knowledge from previously experienced tasks to speed up learning on a new task. So far, rese...
Matthijs Snel, Shimon Whiteson
IAT
2003
IEEE
14 years 25 days ago
Integrating Reinforcement Learning, Bidding and Genetic Algorithms
This paper presents a multi-agent reinforcement learning bidding approach (MARLBS) for performing multi-agent reinforcement learning. MARLBS integrates reinforcement learning, bid...
Dehu Qi, Ron Sun