Verwandte Artikel zu Genetic Programming in the Context of Natural Computing

Genetic Programming in the Context of Natural Computing - Softcover

Schölnast, Hubert

 
9783640594764: Genetic Programming in the Context of Natural Computing
Softcover
ISBN 10: 3640594762 ISBN 13: 9783640594764
Verlag: GRIN Verlag, 2010

Inhaltsangabe

Bachelor Thesis from the year 2009 in the subject Computer Science - Programming, grade: 1, University of Applied Sciences Technikum Vienna (Informations- und Kommunikationssysteme), language: English, abstract: From the sector "Natural Computing" (simulation of natural Phenomena, hardware from nature, nature borrowed methods, etc.), the area "Biological inspired Computing" is selected and described. A systematic literature analysis of this field of research over the past 30 years shows that after a boom in neural networks in the 1990s, in the last five years genetic algorithms, including particularly the methods of genetic programming, came to the foreground. In this heuristic procedure computer programs are optimized in an iterative loop. In the startup phase, programs will be randomly generated. In a frequently recurring cycle, the steps program execution, evaluation of results (determination of fitness); selection and diversification (especially crossover and mutation) are used to "grow" better programs from generation to generation. This work shows criteria to decide in favor of whether or not to use genetic programming. Proven and experimental methods are presented for all phases of the optimization process, and one will find a short survey on how far these methods correlate to their natural role model. This thesis also refers to common problems such as Bloat. A library of methods collected by the author forms a mixture of a cookbook and a toolbox to be used in Genetic Programming. Finally, this thesis provides some examples where with the help of genetic programming award-winning practical applications have been created, which in many cases have outperformed conventionally obtained results.

Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.

Von der hinteren Coverseite

Bachelor Thesis from the year 2009 in the subject Computer Science - Programming, grade: 1, University of Applied Sciences Technikum Vienna (Informations- und Kommunikationssysteme), language: English, abstract: From the sector ¿Natural Computing¿ (simulation of natural Phenomena, hardware from nature, nature borrowed methods, etc.), the area ¿Biological inspired Computing¿ is selected and described. A systematic literature analysis of this field of research over the past 30 years shows that after a boom in neural networks in the 1990s, in the last five years genetic algorithms, including particularly the methods of genetic programming, came to the foreground. In this heuristic procedure computer programs are optimized in an iterative loop. In the startup phase, programs will be randomly generated. In a frequently recurring cycle, the steps program execution, evaluation of results (determination of fitness); selection and diversification (especially crossover and mutation) are used to ¿grow¿ better programs from generation to generation. This work shows criteria to decide in favor of whether or not to use genetic programming. Proven and experimental methods are presented for all phases of the optimization process, and one will find a short survey on how far these methods correlate to their natural role model. This thesis also refers to common problems such as Bloat. A library of methods collected by the author forms a mixture of a cookbook and a toolbox to be used in Genetic Programming. Finally, this thesis provides some examples where with the help of genetic programming award-winning practical applications have been created, which in many cases have outperformed conventionally obtained results.

„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.

Verlag
GRIN Verlag
Erscheinungsdatum
2010
Sprache
Englisch
ISBN 10 
3640594762
ISBN 13 
9783640594764
Einband
Taschenbuch
Anzahl der Seiten
86
Kontakt zum Hersteller
GRIN Publishing GmbH
info@grin.com

Waltherstraße 23
München
80337
Deutschland