Further Comparison between ATNoSFERES and XCSM
Document type :
Communication dans un congrès avec actes
Title :
Further Comparison between ATNoSFERES and XCSM
Author(s) :
Landau, Samuel [Auteur]
Objets et Agents pour Systèmes d'Information et Simulation [OASIS]
Picault, Sebastien [Auteur]
Objets et Agents pour Systèmes d'Information et Simulation [OASIS]
Systèmes Multi-Agents et Comportements [SMAC]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Sigaud, Olivier [Auteur]
Objets et Agents pour Systèmes d'Information et Simulation [OASIS]
Gérard, Pierre [Auteur]
Objets et Agents pour Systèmes d'Information et Simulation [OASIS]
Objets et Agents pour Systèmes d'Information et Simulation [OASIS]
Picault, Sebastien [Auteur]
Objets et Agents pour Systèmes d'Information et Simulation [OASIS]
Systèmes Multi-Agents et Comportements [SMAC]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Sigaud, Olivier [Auteur]
Objets et Agents pour Systèmes d'Information et Simulation [OASIS]
Gérard, Pierre [Auteur]
Objets et Agents pour Systèmes d'Information et Simulation [OASIS]
Scientific editor(s) :
Lanzi, Pier Luca
Stolzmann, Wolfgang
Wilson, Stewart W.
Stolzmann, Wolfgang
Wilson, Stewart W.
Conference title :
IWLCS 2002 - 5th International Workshop on Learning Classifier Systems
City :
Granada
Country :
Espagne
Start date of the conference :
2002-09
Journal title :
Lecture Notes in Computer Science
Publisher :
Springer
Publication date :
2002
English keyword(s) :
ATN
internal state generalization
perceptual aliazing
Learning Classifier Systems
Evolutionary Algorithms
internal state generalization
perceptual aliazing
Learning Classifier Systems
Evolutionary Algorithms
HAL domain(s) :
Informatique [cs]/Système multi-agents [cs.MA]
Informatique [cs]/Apprentissage [cs.LG]
Informatique [cs]/Intelligence artificielle [cs.AI]
Informatique [cs]/Apprentissage [cs.LG]
Informatique [cs]/Intelligence artificielle [cs.AI]
English abstract : [en]
In this paper we present ATNoSFERES, a new framework based on an indirect encoding Genetic Algorithm which builds finite-state automata controllers able to deal with perceptual aliazing. In the context of our ongoing line ...
Show more >In this paper we present ATNoSFERES, a new framework based on an indirect encoding Genetic Algorithm which builds finite-state automata controllers able to deal with perceptual aliazing. In the context of our ongoing line of research, we compare it with XCSM, a memory-based extension of the most studied Learning Classifier System, XCS, through two benchmark experiments. We focus in particular on internal state generalization, and add special purpose features to ATNoSFERES to fulfill that comparison. We then discuss the role played by internal state generalization in the experiments studied.Show less >
Show more >In this paper we present ATNoSFERES, a new framework based on an indirect encoding Genetic Algorithm which builds finite-state automata controllers able to deal with perceptual aliazing. In the context of our ongoing line of research, we compare it with XCSM, a memory-based extension of the most studied Learning Classifier System, XCS, through two benchmark experiments. We focus in particular on internal state generalization, and add special purpose features to ATNoSFERES to fulfill that comparison. We then discuss the role played by internal state generalization in the experiments studied.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Collections :
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