Mobile Robots: The Evolutionary Approach, Leandro dos Santos Coelho

Автор: Ying-ping Chen
Название: Exploitation of Linkage Learning in Evolutionary Algorithms
ISBN: 3642128335 ISBN-13(EAN): 9783642128332
Издательство: Springer
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Цена: 23757.00 р.
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Описание: The exploitation of linkage learning is enhancing the performance of evolutionary algorithms. This monograph examines recent progress in linkage learning, with a series of focused technical chapters that cover developments and trends in the field.

Автор: Jeng-Shyang Pan; Jerry Chun-Wei Lin; Chia-Hung Wan
Название: Genetic and Evolutionary Computing
ISBN: 3319484893 ISBN-13(EAN): 9783319484891
Издательство: Springer
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Цена: 22359.00 р.
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Описание: The conference was co-sponsored by Springer, Fujian University of Technology in China, the University of Computer Studies in Yangon, University of Miyazaki in Japan, National Kaohsiung University of Applied Sciences in Taiwan, Taiwan Association for Web Intelligence Consortium, and VSB-Technical University of Ostrava, Czech Republic.

Автор: Carlos M. Fonseca; Xavier Gandibleux; Jin-Kao Hao;
Название: Evolutionary Multi-Criterion Optimization
ISBN: 3642010199 ISBN-13(EAN): 9783642010194
Издательство: Springer
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Цена: 14673.00 р.
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Описание: Constitutes the refereed proceedings of the 5th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2009, held in Nantes, France in April 2009. This book presents 39 revised full papers together with 5 invited talks that were reviewed and selected from 72 submissions.

Автор: Bechikh
Название: Recent Advances in Evolutionary Multi-objective Optimization
ISBN: 3319429779 ISBN-13(EAN): 9783319429779
Издательство: Springer
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Описание: This book covers the most recent advances in the field of evolutionary multiobjective optimization. With the aim of drawing the attention of up-and coming scientists towards exciting prospects at the forefront of computational intelligence, the authors have made an effort to ensure that the ideas conveyed herein are accessible to the widest audience. The book begins with a summary of the basic concepts in multi-objective optimization. This is followed by brief discussions on various algorithms that have been proposed over the years for solving such problems, ranging from classical (mathematical) approaches to sophisticated evolutionary ones that are capable of seamlessly tackling practical challenges such as non-convexity, multi-modality, the presence of multiple constraints, etc. Thereafter, some of the key emerging aspects that are likely to shape future research directions in the field are presented. These include: optimization in dynamic environments, multi-objective bilevel programming, handling high dimensionality under many objectives, and evolutionary multitasking. In addition to theory and methodology, this book describes several real-world applications from various domains, which will expose the readers to the versatility of evolutionary multi-objective optimization.

Автор: Ernesto Sanchez; Giovanni Squillero; Alberto Tonda
Название: Industrial Applications of Evolutionary Algorithms
ISBN: 364244346X ISBN-13(EAN): 9783642443466
Издательство: Springer
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Описание: Ideal as a reference both for experienced users and novices, this publication combines a thorough introduction to evolutionary computation with details of its application to real-world problems and advice on tackling a wealth of issues in its implementation.

Автор: ?scar Martinez Mozos
Название: Semantic Labeling of Places with Mobile Robots
ISBN: 3642112099 ISBN-13(EAN): 9783642112096
Издательство: Springer
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Цена: 18284.00 р.
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Описание: Service robots often work in indoor environments divided into rooms, corridors and doorways. This book presents several approaches to enable a mobile robot to categorize places indoors. Many approaches come from areas of pattern recognition and classification.

Автор: Ruhul A. Sarker; Tapabrata Ray
Название: Agent-Based Evolutionary Search
ISBN: 3642134246 ISBN-13(EAN): 9783642134241
Издательство: Springer
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Описание: Presenting state-of-the-art theory and practice in the field, this volume includes novel frameworks, a convergence and complexity analysis, and real-world applications. It aims to raise awareness of this effective method of enhancing evolutionary algorithms.