Evolution as Computation - DIMACS Workshop, Princeton, January 1999

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.

Relazione

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)

Dettagli sul prodotto

• Con la collaborazione di: Laura F. Landweber (Editore), Erik Winfree (Editore)
• Editore: Springer, Berlin
• Lingue: Inglese
• Formato: Tascabile
• Pubblicazione: 22.12.2012
• EAN: 9783642630811
• ISBN: 978-3-642-63081-1
• Pagine: 333
• Illustrazioni: XV, 333 p.
• Serie: Natural Computing Series
• Categorie: Scienze naturali, medicina, informatica, tecnica > Informatica, EDP > Informatica; C, Algorithms, Artificial Intelligence, computer science, bioinformatics, chemistry, Biology, life sciences, Theory of Computation, pattern recognition, Computational Mathematics and Numerical Analysis, Algorithms & data structures, Computer mathematics, Numerical analysis, Automated Pattern Recognition, Information technology: general issues, Algorithm Analysis and Problem Complexity, Computational and Systems Biology, Chemoinformatics, Computational Chemistry, Computer Applications in Chemistry, Computational biology, Computer Appl. in Life Sciences