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Towards Fuzzy Learning Classifier Systems: Theory and Application of the Reinforcement Learning, Fuzzy Logic and Learning Classifier Systems - Softcover
Inhaltsangabe
This work aims to provide some new view on the learning of the rule-based systems and explore some possibilities of the autonomous processing of knowledge. Theoretical focus is given on the reinforcement learning, learning classifier systems and fuzzy logic. The second main part of the book proposes an application of the described theory as a new form of a learning rule-based system, suitable for solving tasks in the field of robotics or other problems, where a series of actions is being searched. The proposed approach is evaluated on a set of model problems. In the conclusion, weak sides and necessary improvements are discussed. The book aims to be a small step in the whole process of building an intelligent system - it puts together some ideas in hope that it will be inspiring for others to advance state the art a little more.
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Reseña del editor
This work aims to provide some new view on the learning of the rule-based systems and explore some possibilities of the autonomous processing of knowledge. Theoretical focus is given on the reinforcement learning, learning classifier systems and fuzzy logic. The second main part of the book proposes an application of the described theory as a new form of a learning rule-based system, suitable for solving tasks in the field of robotics or other problems, where a series of actions is being searched. The proposed approach is evaluated on a set of model problems. In the conclusion, weak sides and necessary improvements are discussed. The book aims to be a small step in the whole process of building an intelligent system - it puts together some ideas in hope that it will be inspiring for others to advance state the art a little more.
Biografía del autor
Daniel Hládek is a researcher at the Technical University of Košice, Slovakia at the Department of Electronics and Multimedia Telecommunications.Ján Vaščák is an Assistant Professor at the Department of Cybernetics and Artificial Intelligence. Peter Sinčák is a full professor at the same department.
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Towards Fuzzy Learning Classifier Systems
Verlag:
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3847311352
ISBN 13: 9783847311355
Neu
Softcover
Anbieter: moluna, Greven, Deutschland
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Zustand: New. Artikel-Nr. 5509243
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Towards Fuzzy Learning Classifier Systems
Verlag:
LAP LAMBERT Academic Publishing Feb 2012, 2012
ISBN 10: 3847311352
ISBN 13: 9783847311355
Neu
Taschenbuch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. Neuware -This work aims to provide some new view on the learning of the rule-based systems and explore some possibilities of the autonomous processing of knowledge. Theoretical focus is given on the reinforcement learning, learning classifier systems and fuzzy logic. The second main part of the book proposes an application of the described theory as a new form of a learning rule-based system, suitable for solving tasks in the field of robotics or other problems, where a series of actions is being searched. The proposed approach is evaluated on a set of model problems. In the conclusion, weak sides and necessary improvements are discussed. The book aims to be a small step in the whole process of building an intelligent system - it puts together some ideas in hope that it will be inspiring for others to advance state the art a little more.Books on Demand GmbH, Überseering 33, 22297 Hamburg 124 pp. Englisch. Artikel-Nr. 9783847311355
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