Beskrivning
This work delves into the fascinating intersection of artificial intelligence and evolutionary science. The authors explore the principles of natural evolution and how these concepts can be harnessed to create robust computer systems that learn and adapt over time. Through a rigorous examination of evolutionary algorithms and their applications, they illustrate the potential for these systems to solve complex problems across various domains.
Each chapter is richly laced with insights into the design, implementation, and effectiveness of evolutionary models in computational environments. The collaborative effort of experts in the field provides a multi-faceted understanding of how intelligent systems can evolve, innovate, and improve autonomously.
Readers will find both theoretical discussions and practical examples, giving them a comprehensive overview of the capabilities and future directions of intelligent evolutionary systems. This book serves as a valuable resource for researchers, practitioners, and anyone curious about the convergence of biology and computer science.
Each chapter is richly laced with insights into the design, implementation, and effectiveness of evolutionary models in computational environments. The collaborative effort of experts in the field provides a multi-faceted understanding of how intelligent systems can evolve, innovate, and improve autonomously.
Readers will find both theoretical discussions and practical examples, giving them a comprehensive overview of the capabilities and future directions of intelligent evolutionary systems. This book serves as a valuable resource for researchers, practitioners, and anyone curious about the convergence of biology and computer science.
Bokdetaljer
Format
Inbunden
Sidor
227 sidor
Språk
Engelska
Publicerad
Mar 13, 2009
Förlag
Springer
ISBN-10
3540959777
ISBN-13
9783540959779