Evolution as Computation

Landweber, Laura F. [Editor]; Winfree, Erik [Editor];

ISBN 10: 3540667091 / ISBN 13: 9783540667094

Published by Springer, 2002

About this Item

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Seller Inventory # Q-3540667091

Bibliographic Details

• Title: Evolution as Computation
• Publisher: Springer
• Publication Date: 2002
• Language: English
• ISBN 10: 3540667091
• ISBN 13: 9783540667094
• Binding: hardcover
• Condition: New
• Weight: 27 ounces

About this title

Synopsis

The study of the genetic basis for evolution has flourished in this century, as well as our understanding of the evolvability and programmability of biological systems. Genetic algorithms meanwhile grew out of the realization that a computer program could use the biologically-inspired processes of mutation, recombination, and selection to solve hard optimization problems. Genetic and evolutionary programming provide further approaches to a wide variety of computational problems. A synthesis of these experiences reveals fundamental insights into both the computational nature of biological evolution and processes of importance to computer science. Topics include biological models of nucleic acid information processing and genome evolution; molecules, cells, and metabolic circuits that compute logical relationships; the origin and evolution of the genetic code; and the interface with genetic algorithms and genetic and evolutionary programming.

From the Back Cover

The study of the genetic basis for evolution has flourished in this century, as well as our understanding of the evolvability and programmability of biological systems. Genetic algorithms meanwhile grew out of the realization that a computer program could use the biologically-inspired processes of mutation, recombination, and selection to solve hard optimization problems. Genetic and evolutionary programming provide further approaches to a wide variety of computational problems. A synthesis of these experiences reveals fundamental insights into both the computational nature of biological evolution and processes of importance to computer science. Topics include biological models of nucleic acid information processing and genome evolution; molecules, cells, and metabolic circuits that compute logical relationships; the origin and evolution of the genetic code; and the interface with genetic algorithms, genetic and evolutionary programming. This research combines theory and experiments to understand the computations that take place in cells and the combinatorial processes that drive evolution at the molecular level.