1.

Record Nr.

UNINA990003938080403321

Autore

Murtha, Thomas P.

Titolo

Managing new industry creation : global knowledge formation and entrepreneurship in high technology / Thomas P.Murtha, Stefanie Ann Lenway, Jeffrey A.Hart

Pubbl/distr/stampa

Stanford : Stanford business, 2001

ISBN

0-8047-4228-6

Descrizione fisica

xvi, 269 p. ; 23 cm

Locazione

ECA

Collocazione

1-6-462-TI

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

2.

Record Nr.

UNINA9910254170503321

Autore

Kramer Oliver

Titolo

Genetic Algorithm Essentials / / by Oliver Kramer

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017

ISBN

3-319-52156-X

Edizione

[1st ed. 2017.]

Descrizione fisica

1 online resource (IX, 92 p. 38 illus. in color.)

Collana

Studies in Computational Intelligence, , 1860-949X ; ; 679

Disciplina

519.7

Soggetti

Computational intelligence

Artificial intelligence

Computational Intelligence

Artificial Intelligence

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references and index.



Nota di contenuto

Part I: Foundations -- Introduction -- Genetic Algorithms -- Parameters -- Part II: Solution Spaces -- Multimodality -- Constraints -- Multiple Objectives -- Part III: Advanced Concepts -- Theory -- Machine Learning -- Applications -- Part IV: Ending -- Summary and Outlook -- Index -- References.

Sommario/riassunto

This book introduces readers to genetic algorithms (GAs) with an emphasis on making the concepts, algorithms, and applications discussed as easy to understand as possible. Further, it avoids a great deal of formalisms and thus opens the subject to a broader audience in comparison to manuscripts overloaded by notations and equations. The book is divided into three parts, the first of which provides an introduction to GAs, starting with basic concepts like evolutionary operators and continuing with an overview of strategies for tuning and controlling parameters. In turn, the second part focuses on solution space variants like multimodal, constrained, and multi-objective solution spaces. Lastly, the third part briefly introduces theoretical tools for GAs, the intersections and hybridizations with machine learning, and highlights selected promising applications.