General-Purpose Optimization Through Information Maximization

Language: English

Published by Springer Berlin Heidelberg Aug 2021, 2021

366262009X / 9783662620090

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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.

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This item is printed on demand - it takes 3-4 days longer - Neuware -This book examines the mismatch betweendiscrete programs,which lie at the center ofmodern applied mathematics, and the continuous space phenomena they simulate. The author considers whether we can imagine continuous spacesof programs, and asks what thestructure of such spaceswould beand how they would beconstituted. He proposesa functional analysisof program spaces focused through the lens of iterative optimization.The author begins with the observation that optimization methods such as Genetic Algorithms, Evolution Strategies, and Particle Swarm Optimization can be analyzed as Estimation of Distributions Algorithms (EDAs) in that they can be formulated as conditional probability distributions. The probabilities themselves are mathematical objects that can be compared and operated on, and thus many methods in Evolutionary Computation can be placed in a shared vector space and analyzed using techniques of functional analysis. The core ideas of this book expand from that concept, eventually incorporating all iterative stochastic search methods, including gradient-based methods. Inspired by work on Randomized Search Heuristics, the author covers all iterative optimization methods and not just evolutionary methods. The No Free Lunch Theorem is viewed as a useful introduction to the broader field of analysis that comes from developing a shared mathematical space for optimization algorithms. The author brings in intuitions from several branches of mathematics such as topology, probability theory, and stochastic processes and provides substantial background material to make the work as self-contained as possible.The book will be valuable for researchers in the areas of global optimization, machine learning, evolutionary theory, and control theory. 580 pp. Englisch.

Seller Inventory # 9783662620090

Title
General-Purpose Optimization Through Information Maximization
Author
Alan J. Lockett
Publisher
Springer Berlin Heidelberg Aug 2021
Publication year
2021
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
366262009X
ISBN 13
9783662620090
Item weight
867 grams
Dimensions
235x155x32 mm

BuchWeltWeit Ludwig Meier e.K.

Bergisch Gladbach, Germany

5-star seller

AbeBooks seller since January 11, 2012

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BuchWeltWeit Ludwig Meier e.K.

Germany