Evolutionary Algorithms and Chaotic Systems

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.

Klappentext

This book discusses the mutual intersection of two fields of research: evolutionary computation, which can handle tasks such as control of various chaotic systems, and deterministic chaos, which is investigated as a behavioral part of evolutionary algorithms.

Inhalt

Theory.- Motivation for Application of Evolutionary Computation to Chaotic Systems.- Evolutionary Algorithms for Chaos Researchers.- Chaos Theory for Evolutionary Algorithms Researchers.- Evolutionary Algorithms and the Edge of Chaos.- Applications.- Evolutionary Design of Chaos Control in 1D.- Evolutionary Control of CML Systems.- Chaotic Systems Reconstruction.- Evolutionary Reconstruction of Chaotic Systems.- Cryptography Based on Spatiotemporal Chaotic Systems.- Evolutionary Decryption of Chaotically Encrypted Information.- Chaos Synthesis by Evolutionary Algorithms.- Evolutionary Synchronization of Chaotic Systems.- Evolutionary Optimization and Dynamic Fitness Landscapes.- Controller Parameters Optimization on a Representative Set of Systems Using Deterministic-Chaotic-Mutation Evolutionary Algorithms.- Chaotic Attributes and Permutative Optimization.- Frontiers.