Learning environment dynamics from self-adaptation. A preliminary investigation - INRIA - Institut National de Recherche en Informatique et en Automatique Accéder directement au contenu
Communication Dans Un Congrès Année : 2005

Learning environment dynamics from self-adaptation. A preliminary investigation

Amine Boumaza
  • Fonction : Auteur
  • PersonId : 830929

Résumé

We present an experimental study that shows a relationship between the dynamics of the environment and the adaptation of strategy parameters. Experiments conducted on two adaptive evolutionary strategies SA-ES and CMA-ES on the dynamic sphere function, show that the nature of the movements of the function's optimum are reflected in the evolution of the mutation steps. Three types of movements are presented: constant, linear and quadratic velocity, in all, the evolution of mutation steps during adaptation reflect distinctly the nature of the movements. Furthermore with CMA-ES, the direction of movement of the optimum can be extracted.
Fichier principal
Vignette du fichier
evodop05.pdf (304.13 Ko) Télécharger le fichier

Dates et versions

inria-00000618 , version 1 (08-11-2005)

Identifiants

  • HAL Id : inria-00000618 , version 1

Citer

Amine Boumaza. Learning environment dynamics from self-adaptation. A preliminary investigation. GECCO'05 Workshop on Evolutionary Algorithms for Dynamic Optimization Problems - EvoDOP, Jun 2005, Washington DC/USA. ⟨inria-00000618⟩
96 Consultations
128 Téléchargements

Partager

Gmail Facebook X LinkedIn More