Reeves (mathematical and information sciences, Coventry U., UK) and Rowe (computer science, U. of Birmingham, UK) describe the traditional theory of schemata and the implications of the no-free-lunch theorem before turning to the different perspectives on genetic algorithms, including Markov chain theory, and the dynamic and macroscopic behavior of genetic algorithms. Two chapters are devoted to statistical methods in experimental design and in heuristic search methods. Annotation (c) Book News, Inc., Portland, OR (booknews.com)
Genetic Algorithms: Principles and Perspectives: A Guide to GA Theory is a survey of some important theoretical contributions, many of which have been proposed and developed in the Foundations of Genetic Algorithms series of workshops. However, this theoretical work is still rather fragmented, and the authors believe that it is the right time to provide the field with a systematic presentation of the current state of theory in the form of a set of theoretical perspectives. The authors do this in the interest of providing students and researchers with a balanced foundational survey of some recent research on GAs. The scope of the book includes chapter-length discussions of Basic Principles, Schema Theory, "No Free Lunch", GAs and Markov Processes, Dynamical Systems Model, Statistical Mechanics Approximations, Predicting GA Performance, Landscapes and Test Problems.
Daugiau apie elektronines knygas