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.
| ISBN: | 9783642064135 |
| Publication date: | 25th November 2010 |
| Author: | Larry Bull, Tim Kovacs |
| Publisher: | Springer an imprint of Springer Berlin Heidelberg |
| Format: | Paperback |
| Pagination: | 336 pages |
| Series: | Studies in Fuzziness and Soft Computing |
| Genres: |
Maths for engineers Computational biology / bioinformatics Applied mathematics Artificial intelligence |
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.
Foundations of Learning Classifier Systems features in the following genres: Maths for engineers, Computational biology / bioinformatics, Applied mathematics, Artificial intelligence
Paperback, Hardback. Not Available.
Foundations of Learning Classifier Systems was written by Larry Bull, Tim Kovacs and published by Springer an imprint of Springer Berlin Heidelberg
Foundations of Learning Classifier Systems has 336 pages
Yes it is part of Studies in Fuzziness and Soft Computing series