Evolution as Computation
DIMACS Workshop, Princeton, January 1999
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Beschreibung
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.
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.
A unique interdisciplinary link between a wide range of subjects in computer science and biology Ideally suited for graduate students entering this new field Includes supplementary material: sn.pub/extras
Autor*in
Laura F. Landweber
Themen in »Evolution as Computation«
algorithms evolution genetic algorithm genetic algorithms genome mutation optimization the origin algorithm analysis and problem complexity
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From the reviews:
"Most algorithms used within the domain of so-called ‘soft-computing’ were directly inspired by our knowledge of biological ‘computation’ in living organisms. … This book … as such, reflects the present state of the art. … The reading of the individual contributions should be very useful, both for the mathematician and the computer scientist, and is highly recommended since it erodes the trust in old and consolidated conceptions." (E. Pessa, Mathematical Reviews, 2004 i)
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