Cartesian Genetic Programming (CGP) is a highly effective and increasingly popular form of genetic programming. It represents programs in the form of directed graphs, and a particular characteristic is that it has a highly redundant genotype-phenotype mapping, in that genes can be noncoding. It has spawned a number of new forms, each improving on the efficiency, among them modular, or embedded, CGP, and self-modifying CGP. It has been applied to many problems in both computer science and applied sciences.
This book contains chapters written by the leading figures in the...
Cartesian Genetic Programming (CGP) is a highly effective and increasingly popular form of genetic programming. It represents programs in the form ...
Self-organisation, self-regulation, self-repair and self-maintenance are promising conceptual approaches for dealing with complex distributed interactive software and information-handling systems. Self-organising applications dynamically change their functionality and structure without direct user intervention, responding to changes in requirements and the environment. This is the first book to offer an integrated view of self-organisation technologies applied to distributed systems, particularly focusing on multiagent systems.
The editors developed this integrated book...
Self-organisation, self-regulation, self-repair and self-maintenance are promising conceptual approaches for dealing with complex distr...
This book covers the basic theory, practical details and advanced research of the implementation of evolutionary methods on physical substrates. Most of the examples are from electronic engineering applications, including transistor-level design and system-level implementation. The authors present an overview of the successes achieved, and the book will act as a point of reference for both academic and industrial researchers.
This book covers the basic theory, practical details and advanced research of the implementation of evolutionary methods on physical substrates. Most ...
This book explains the theory and application of evolutionary computer vision, a new paradigm where challenging vision problems can be approached using the techniques of evolutionary computing.
This book explains the theory and application of evolutionary computer vision, a new paradigm where challenging vision problems can be approached usin...
Evolutionary algorithms (EAs) are metaheuristics that learn from natural collective behavior and are applied to solve optimization problems in domains such as scheduling, engineering, bioinformatics, and finance. Such applications demand acceptable solutions with high-speed execution using finite computational resources. Therefore, there have been many attempts to develop platforms for running parallel EAs using multicore machines, massively parallel cluster machines, or grid computing environments. Recent advances in general-purpose computing on graphics processing units (GPGPU) have...
Evolutionary algorithms (EAs) are metaheuristics that learn from natural collective behavior and are applied to solve optimization problems in doma...
This volume, which includes the author's own software package, tracks the development of evolutionary computation since 1990, with detailed evaluations of key approaches, pseudocode representations of each algorithm, and industry-applicable BBOB benchmarking.
This volume, which includes the author's own software package, tracks the development of evolutionary computation since 1990, with detailed evaluation...
Theoretical tools and insights from discrete mathematics, theoretical computer science, and topology now play essential roles in our understanding of vital biomolecular processes. The related methods are now employed in various fields of mathematical biology as instruments to "zoom in" on processes at a molecular level. This book contains expository chapters on how contemporary models from discrete mathematics - in domains such as algebra, combinatorics, and graph and knot theories - can provide perspective on biomolecular problems ranging from data analysis, molecular and gene arrangements...
Theoretical tools and insights from discrete mathematics, theoretical computer science, and topology now play essential roles in our understanding of ...
This book describes methods for incorporating problem knowledge in evolutionary algorithms and other metaheuristics, and shows how statistical methods can use experimental data to enhance the performance of existing metaheuristics in a systematic way.
This book describes methods for incorporating problem knowledge in evolutionary algorithms and other metaheuristics, and shows how statistical methods...
The overall structure of this new edition is three-tier: Part I presents the basics, Part II is concerned with methodological issues, and Part III discusses advanced topics.
The overall structure of this new edition is three-tier: Part I presents the basics, Part II is concerned with methodological issues, and Part III dis...
This book covers the basic theory, practical details and advanced research of the implementation of evolutionary methods on physical substrates. The authors present an overview of the successes achieved, and the book will act as a point of reference for both academic and industrial researchers.
This book covers the basic theory, practical details and advanced research of the implementation of evolutionary methods on physical substrates. The a...
