Synopsis
Ever since the historical discovery of the now-famous Lorenz system in 1963, a large number of nonlinear systems that can produce chaos have been - served,constructedandanalyzed. Infact,chaostheoryhasbecomeindispe- able for science and engineering at all levels of research today. The most - tive recent researchincludes chaos controland chaos synchronization,among others, with a visible trend toward real-world applications. The book titled "Evolutionary Algorithms and Chaotic Systems", edited by Ivan Zelinka, Sergej Celikovsky, Hendrik Richter and Guanrong Chen, is a timely volume to be welcome by the chaos community as well as c- putational intelligence community and beyond. This book is devoted to the studies of common and related subjects in two intensive research ?elds of chaos theory and evolutionary computation. It was not typical that e- lutionary computing techniques are used for e?ective chaos control, chaos synchronization,chaosidenti?cation, andin particularfor chaosanalysisand synthesis, therefore this edition of collective state-of-the-art articles on such interdisciplinarysubjects isespecially valuableforthescienti?candengine- ing communities. For these reasons, I enthusiastically recommend this book to our scientists and engineers working in the ?elds of nonlinear dynamics, evolutionary algorithms, control theory, circuits and systems, and scienti?c computing alike. University of California at Berkeley, September 2009 Leon O. Chua Preface Deterministic chaos is a fairly active area of research in the last few decades. Well known chaotic attractors can even be produced by some simple three-dimensional autonomous systems of ordinary di?erential equations, for example the Lorenz system, which originates from modelling of atmospheric dynamics.
From the Back Cover
This book discusses the mutual intersection of two interesting fields of research, i.e. deterministic chaos and evolutionary computation. Evolutionary computation which are able to handle tasks such as control of various chaotic systems and synthesis of their structure are explored, while deterministic chaos is investigated as a behavioral part of evolutionary algorithms.
This book is targeted for a number of audiences. Firstly, it will be an instructional material for senior undergraduate and entry-point graduate students in computer science, physics, applied mathematics, and engineering, who are working in the area of deterministic chaos and evolutionary algorithms. Secondly, researchers who desire to know how to apply evolutionary techniques on chaos control as well as researchers interested in the emergence of chaos in evolutionary algorithms will find this book a very useful tool and starting point. And finally, this book can be viewed as a resource handbook and material for practitioners who want to apply these methods that solve practical problems to their challenging applications.
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