Logo

Evolved to Win by Moshe Sipper

Small book cover: Evolved to Win

Evolved to Win
by

Publisher: Lulu.com
ISBN-13: 9781470972837
Number of pages: 193

Description:
Moshe Sipper and his group have produced a plethora of award-winning results, in numerous games of diverse natures, evidencing the success and efficiency of evolutionary algorithms in general -- and genetic programming in particular -- at producing top-notch, human-competitive game strategies. From classic chess and checkers, through simulated car racing and virtual warfare, to mind-bending puzzles, this book serves both as a tour de force of the research landscape and as a guide to the application of evolutionary computation within the domain of games.

Home page url

Download or read it online for free here:
Download link
(1.9MB, PDF)

Similar books

Book cover: Advances in Evolutionary AlgorithmsAdvances in Evolutionary Algorithms
by - InTech
With the recent trends towards massive data sets and significant computational power, evolutionary computation is becoming much more relevant to practice. The book presents recent improvements, ideas and concepts in a part of a huge EA field.
(15302 views)
Book cover: Advances in Genetic Programming, Vol. 3Advances in Genetic Programming, Vol. 3
by - The MIT Press
Genetic programming is a form of evolutionary computation that evolves programs and program-like executable structures for developing reliable applications. This volume highlights the recent technical advances in this increasingly popular field.
(9515 views)
Book cover: Evolutionary AlgorithmsEvolutionary Algorithms
by - InTech
Evolutionary algorithms are successively applied to wide optimization problems in the engineering, marketing, operations research, and social science, such as include scheduling, genetics, material selection, structural design and so on.
(10744 views)
Book cover: Genetic Programming: New Approaches and Successful ApplicationsGenetic Programming: New Approaches and Successful Applications
by - InTech
Genetic programming (GP) is a branch of Evolutionary Computing that aims the automatic discovery of programs to solve a given problem. Since its appearance, in the earliest nineties, GP has become one of the most promising paradigms ...
(9736 views)