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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...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor Corporativo: | |
| Otros Autores: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2005.
|
| Edición: | 1st ed. 2005. |
| Colección: | Studies in Fuzziness and Soft Computing,
183 |
| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
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| 245 | 1 | 0 | |a Foundations of Learning Classifier Systems |h [electronic resource] / |c edited by Larry Bull, Tim Kovacs. |
| 250 | |a 1st ed. 2005. | ||
| 264 | 1 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg : |b Imprint: Springer, |c 2005. | |
| 300 | |a VI, 336 p. |b online resource. | ||
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| 490 | 1 | |a Studies in Fuzziness and Soft Computing, |x 1860-0808 ; |v 183 | |
| 505 | 0 | |a 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? | |
| 520 | |a 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 computation) tailored for a classifier systems audience and written by acknowledged authorities in their area - as well as a relevant historical original work by John Holland. | ||
| 650 | 0 | |a Engineering mathematics. | |
| 650 | 0 | |a Engineering-Data processing. | |
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 0 | |a Mathematics. | |
| 650 | 0 | |a Bioinformatics. | |
| 650 | 1 | 4 | |a Mathematical and Computational Engineering Applications. |
| 650 | 2 | 4 | |a Artificial Intelligence. |
| 650 | 2 | 4 | |a Applications of Mathematics. |
| 650 | 2 | 4 | |a Bioinformatics. |
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| 700 | 1 | |a Kovacs, Tim. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
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| 830 | 0 | |a Studies in Fuzziness and Soft Computing, |x 1860-0808 ; |v 183 | |
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