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Communication Dans Un Congrès Année : 2001

Adding a Generalization Mechanism to YACS

Résumé

A new and original trend in the Learning Classifier System (LCS) framework is focussed on latent learning. These new LCSs call upon classifiers with a [condition], an [action] and an [effect] part. In the LCS framework, the latent learning process is in charge of discovering classifiers which are able to anticipate accurately the consequences of actions under some conditions. Accordingly, this process builds a model of the dynamics of the environment. This paper describes how YACS performs latent learning, and how it is enhanced by a dedicated generalization process which offers an alternative to Genetic Algorithms.
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Dates et versions

hal-01571789 , version 1 (03-08-2017)

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  • HAL Id : hal-01571789 , version 1

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Pierre Gérard, Olivier Sigaud. Adding a Generalization Mechanism to YACS. GECCO 2001 - 3rd Annual Conference on Genetic and Evolutionary Computation, Jul 2001, San Francisco, CA, United States. pp.951-957. ⟨hal-01571789⟩
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