Foundations of learning classifier systems
This volume brings together recent theoretical work in Learning Classifier Systems (LCS), which is a Machine Learning technique combining Genetic Algorithms and Reinforcement Learning. It includes self-contained background chapters on related fields (reinforcement learning and evolutionary computati...
Gorde:
| Egile nagusia: | |
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| Beste egile batzuk: | , , |
| Formatua: | Livre numérique |
| Hizkuntza: | Anglais |
| Argitaratua: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Edizioa: | 1st ed. 2005. |
| Saila: | Studies in Fuzziness and Soft Computing
183 |
| Sarrera elektronikoa: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Oharra: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Foundations of learning classifier systems, Larry Bull, Tim Kovacs, Berlin, Springer-Verlag, 2005, 1 vol. (VI-336 p.), Studies in fuzziness and soft computing, 3-540-25073-5 • Foundations of Learning Classifier Systems, Texte imprimé, 9783540808282 • Foundations of Learning Classifier Systems, Texte imprimé, 9783642064135 • Foundations of learning classifier systems, Larry Bull, Tim Kovacs, Berlin, Springer-Verlag, 2005, 1 vol. (VI-336 p.), Studies in fuzziness and soft computing, 3-540-25073-5 |
Aurkibidea:
- Section 1 Rule Discovery. Population Dynamics of Genetic Algorithms. Approximating Value Functions in Classifier Systems. Two Simple Learning Classifier Systems. Computational Complexity of the XCS Classifier System. An Analysis of Continuous-Valued Representations for Learning Classifier Systems Section 2 Credit Assignment. Reinforcement Learning: a Brief Overview. A Mathematical Framework for Studying Learning Classifier Systems. Rule Fitness and Pathology in Learning Classifier Systems. Learning Classifier Systems: A Reinforcement Learning Perspective. Learning Classifier Systems with Convergence and Generalization Section 3 Problem Characterization. On the Classification of Maze Problems. What Makes a Problem Hard?