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Foundations of Learning Classifier Systems -

Foundations of Learning Classifier Systems

Larry Bull, Tim Kovacs (Herausgeber)

Buch | Softcover
VI, 336 Seiten
2010 | Softcover reprint of hardcover 1st ed. 2005
Springer Berlin (Verlag)
978-3-642-06413-5 (ISBN)
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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.

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?

Erscheint lt. Verlag 25.11.2010
Reihe/Serie Studies in Fuzziness and Soft Computing
Zusatzinfo VI, 336 p.
Verlagsort Berlin
Sprache englisch
Maße 155 x 235 mm
Gewicht 521 g
Themenwelt Mathematik / Informatik Mathematik Angewandte Mathematik
Technik
Schlagworte Adaptation • algorithm • algorithms • Calculus • classification • Complexity • Dynamics • Evolution • evolutionary computation • Evolutionary Computing • Genetic algorithms • Knowledge • learning • machine learning • Mathematica • Reinforcement Learning • Soft Computing
ISBN-10 3-642-06413-2 / 3642064132
ISBN-13 978-3-642-06413-5 / 9783642064135
Zustand Neuware
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