Bücher der Reihe Natural Computing Series

The field of biologically inspired computation has coexisted with mainstream computing since the 1930s, and the pioneers in this area include Warren McCulloch, Walter Pitts, Robert Rosen, Otto Schmitt, Alan Turing, John von Neumann and Norbert Wiener.

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. and the interface with genetic algorithms and genetic and evolutionary programming.

Finally, the book presents diverse applications of self-organising software, such as constraint satisfaction, trust management, image recognition and networking.The book will be of interest to researchers working on emergent phenomena and adaptive systems.

Cartesian Genetic Programming (CGP) is a highly effective and increasingly popular form of genetic programming.

This book provides a collection of fourty articles containing new material on both theoretical aspects of Evolutionary Computing (EC), and demonstrating the usefulness/success of it for various kinds of large-scale real world problems.

The field of biologically inspired computation has coexisted with mainstream computing since the 1930s, and the pioneers in this area include Warren McCulloch, Walter Pitts, Robert Rosen, Otto Schmitt, Alan Turing, John von Neumann and Norbert Wiener.

The natural world is full of wonderful examples of its successes, from engineering design feats such as powered flight, to the design of complex optical systems such as the mammalian eye, to the merely stunningly beautiful designs of orchids or birds of paradise.

The book's contributing authors are among the top researchers in swarm intelligence. Introductory chapters deal with the biological foundations, optimization, swarm robotics, and applications in new-generation telecommunication networks, while the second part contains chapters on more specific topics of swarm intelligence research.

Massively Parallel Evolutionary Computation on GPGPUs

Presents new mathematical and computational models as well as statistical methods for the solution of fundamental problems in the biosciences. Describes how to find regularities among empirical data, as well as conceptual models and theories.

Metaheuristics, and evolutionary algorithms in particular, are known to provide efficient, adaptable solutions for many real-world problems, but the often informal way in which they are defined and applied has led to misconceptions, and even successful applications are sometimes the outcome of trial and error.

The editors, both leading experts in this field, have assembled a team of researchers to contribute 21 chapters organized into parts on simulated annealing, tabu search, ant colony algorithms, general purpose studies of evolutionary algorithms, applications of evolutionary algorithms, and metaheuristics.

During the first week of September 1999, the Second EvoNet Summer School on Theoretical Aspects of Evolutionary Computing was held at the Middelheim cam pus of the University of Antwerp, Belgium.

The 30 coherently written chapters by leading researchers presented in this anthology are devoted to basic results achieved in computational intelligence since 1997.

Cartesian Genetic Programming (CGP) is a highly effective and increasingly popular form of genetic programming.

The editors, both leading experts in this field, have assembled a team of researchers to contribute 21 chapters organized into parts on simulated annealing, tabu search, ant colony algorithms, general purpose studies of evolutionary algorithms, applications of evolutionary algorithms, and metaheuristics.

The natural world is full of wonderful examples of its successes, from engineering design feats such as powered flight, to the design of complex optical systems such as the mammalian eye, to the merely stunningly beautiful designs of orchids or birds of paradise.

The book's contributing authors are among the top researchers in swarm intelligence. Introductory chapters deal with the biological foundations, optimization, swarm robotics, and applications in new-generation telecommunication networks, while the second part contains chapters on more specific topics of swarm intelligence research.

Details robustness, stability, and performance of Evolutionary Algorithms in dynamic environments

This text examines how multiobjective evolutionary algorithms and related techniques can be used to solve problems, particularly in the disciplines of science and engineering.

This comprehensive book gives an up-to-date survey of the relevant bioinspired computing research fields - such as evolutionary computation, artificial life, swarm intelligence and ant colony algorithms - and examines applications in art, music and design.

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. and the interface with genetic algorithms and genetic and evolutionary programming.

The 30 coherently written chapters by leading researchers presented in this anthology are devoted to basic results achieved in computational intelligence since 1997.

Presents new mathematical and computational models as well as statistical methods for the solution of fundamental problems in the biosciences. Describes how to find regularities among empirical data, as well as conceptual models and theories.