The Theory of Evolution Strategies [electronic resource] /

Evolutionary Algorithms, in particular Evolution Strategies, Genetic Algorithms, or Evolutionary Programming, have found wide acceptance as robust optimization algorithms in the last ten years. Compared with the broad propagation and the resulting practical prosperity in different scientific fields, the theory has not progressed as much. This monograph provides the framework and the first steps toward the theoretical analysis of Evolution Strategies (ES). The main emphasis is on understanding the functioning of these probabilistic optimization algorithms in real-valued search spaces by investigating the dynamical properties of some well-established ES algorithms. The book introduces the basic concepts of this analysis, such as progress rate, quality gain, and self-adaptation response, and describes how to calculate these quantities. Based on the analysis, functioning principles are derived, aiming at a qualitative understanding of why and how ES algorithms work.

Bibliographic Details

Main Authors:	Beyer, Hans-Georg. author., SpringerLink (Online service)
Format:	Texto biblioteca
Language:	eng
Published:	Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2001
Subjects:	Computer science., Computer programming., Algorithms., Artificial intelligence., Bioinformatics., Computational biology., Statistical physics., Dynamical systems., Statistics., Computer Science., Artificial Intelligence (incl. Robotics)., Programming Techniques., Algorithm Analysis and Problem Complexity., Statistical Physics, Dynamical Systems and Complexity., Computer Appl. in Life Sciences., Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.,
Online Access:	http://dx.doi.org/10.1007/978-3-662-04378-3
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