Get Free Shipping on orders over $79
Representations for Genetic and Evolutionary Algorithms : Studies in Fuzziness and Soft Computing - D.E. Goldberg

Representations for Genetic and Evolutionary Algorithms

By: D.E. Goldberg (Foreword by), Franz Rothlauf

Paperback | 18 April 2012

At a Glance

Paperback


$84.99

or 4 interest-free payments of $21.25 with

 or 

Ships in 5 to 7 business days

In the field of genetic and evolutionary algorithms (GEAs), much theory and empirical study has been heaped upon operators and test problems, but problem representation has often been taken as given. This monograph breaks with this tradition and studies a number of critical elements of a theory of representations for GEAs and applies them to the empirical study of various important idealized test functions and problems of commercial import. The book considers basic concepts of representations, such as redundancy, scaling and locality and describes how GEAs'performance is influenced. Using the developed theory representations can be analyzed and designed in a theory-guided manner. The theoretical concepts are used as examples for efficiently solving integer optimization problems and network design problems. The results show that proper representations are crucial for GEAs'success.

More in Artificial Intelligence

AI for Business : A Guide to AI Adoption - Jon Whittle

RRP $49.99

$40.75

18%
OFF
The Singularity is Nearer : When We Merge with AI - Ray Kurzweil

RRP $26.99

$22.99

15%
OFF
Creative Machines : AI, Art & Us - Maya Ackerman

RRP $57.95

$44.75

23%
OFF
New Beginnings : why change is so difficult and how to achieve it - Stefan Klein
The Tech Coup : How to Save Democracy from Silicon Valley - Marietje Schaake
The Shortest History of AI - Toby Walsh

RRP $27.99

$22.75

19%
OFF
Genesis : Artificial Intelligence, Hope, and the Human Spirit - Eric Schmidt
Artificial Intelligence : A Modern Approach, 4th Global Edition - Peter Norvig
Life 3.0 : Being Human in the Age of Artificial Intelligence - Max Tegmark
How We Learn : The New Science of Education and the Brain - Stanislas Dehaene
Handbook of Reinforcement Learning - Todd Mcmullen