EVOLVE ¿ A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation VII

Michael Emmerich

ISBN 10: 3319841335 / ISBN 13: 9783319841335

Editore: Springer International Publishing, Springer International Publishing, 2018

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Druck auf Anfrage Neuware - Printed after ordering - This book comprises nine selected works on numerical and computational methods for solving multiobjective optimization, game theory, and machine learning problems. It provides extended versions of selected papers from various fields of science such as computer science, mathematics and engineering that were presented at EVOLVE 2013 held in July 2013 at Leiden University in the Netherlands. The internationally peer-reviewed papers include original work on important topics in both theory and applications, such as the role of diversity in optimization, statistical approaches to combinatorial optimization, computational game theory, and cell mapping techniques for numerical landscape exploration. Applications focus on aspects including robustness, handling multiple objectives, and complex search spaces in engineering design and computational biology. Codice articolo 9783319841335

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Titolo: EVOLVE ¿ A Bridge between Probability, Set ...

Casa editrice: Springer International Publishing, Springer International Publishing

Data di pubblicazione: 2018

Legatura: Taschenbuch

Condizione: Neu

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Riassunto:

This book comprises nine selected works on numerical and computational methods for solving multiobjective optimization, game theory, and machine learning problems. It provides extended versions of selected papers from various fields of science such as computer science, mathematics and engineering that were presented at EVOLVE 2013 held in July 2013 at Leiden University in the Netherlands. The internationally peer-reviewed papers include original work on important topics in both theory and applications, such as the role of diversity in optimization, statistical approaches to combinatorial optimization, computational game theory, and cell mapping techniques for numerical landscape exploration. Applications focus on aspects including robustness, handling multiple objectives, and complex search spaces in engineering design and computational biology.