Genetic Algorithms and Robotics: A Heuristic Strategy for Optimization

Tom Husband et Yuval Davidor

ISBN 10: 9810202172 / ISBN 13: 9789810202170

Editore: World Scientific Publishing Co Pte Ltd, 1991

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Ancien livre de bibliothèque. Jaquette abîmée. Edition 1991. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Good. Former library book. Damaged dust jacket. Edition 1991. Ammareal gives back up to 15% of this item's net price to charity organizations.

Codice articolo E-843-148

Dati bibliografici

• Titolo: Genetic Algorithms and Robotics: A Heuristic Strategy for Optimization
• Editore: World Scientific Publishing Co Pte Ltd
• Data di pubblicazione: 1991
• Lingua: Inglese
• ISBN 10: 9810202172
• ISBN 13: 9789810202170
• Rilegatura: Hardcover
• Condizione: Bon

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Riassunto

Classical optimization methodologies fall short in very large and complex domains. In this book is suggested a different approach to optimization, an approach which is based on the 'blind' and heuristic mechanisms of evolution and population genetics. The genetic approach to optimization introduces a new philosophy to optimization in general, but particularly to engineering. By introducing the ‘genetic’ approach to robot trajectory generation, much can be learned about the adaptive mechanisms of evolution and how these mechanisms can solve real world problems. It is suggested further that optimization at large may benefit greatly from the adaptive optimization exhibited by natural systems when attempting to solve complex optimization problems, and that the determinism of classical optimization models may sometimes be an obstacle in nonlinear systems.This book is unique in that it reports in detail on an application of genetic algorithms to a real world problem, and explains the considerations taken during the development work. Futhermore, it addresses robotics in two new aspects: the optimization of the trajectory specification which has so far been done by human operators and has not received much attention for both automation and optimization, and the introduction of a heuristic strategy to a field predominated by deterministic strategies.