Marco Tomassini – författare

The authors stress the relative simplicity, efficiency, flexibility of use, and suitability of various approaches used to solve difficult optimization problems. This textbook is a suitable introduction for undergraduate and graduate students, researchers, and professionals in computer science, engineering, and logistics.

Evolutionary algorithms (EAs) is now a mature problem-solving family of heuristics that has found its way into many important real-life problems and into leading-edge scientific research. Spatially structured EAs have different properties than standard, mixing EAs. By virtue of the structured disposition of the population members they bring about new dynamical features that can be harnessed to solve difficult problems faster and more efficiently. This book describes the state of the art in spatially structured EAs by using graph concepts as a unifying theme. The models, their analysis, and their empirical behavior are presented in detail. Moreover, there is new material on non-standard networked population structures such as small-world networks.The book should be of interest to advanced undergraduate and graduate students working in evolutionary computation, machine learning, and optimization. It should also be useful to researchers and professionals working in fields where the topological structures of populations and their evolution plays a role.

This book constitutes the refereed proceedings of the 8th European Conference on Genetic Programming, EuroGP 2005, held in Lausanne, Switzerland in March/April 2005.The 20 revised plenary papers and 14 revised poster papers were carefully reviewed and selected from 64 submissions. Some of the papers deal with foundational, theoretical, or methodological aspects of genetic programming; others focus on applications in various areas, such as computer science, engineering, language processing, biology, and computational design, demonstrating that genetic programming is a powerful and practical problem solving tool.

This book constitutes the refereed proceedings of the 9th European Conference on Genetic Programming, EuroGP 2006, held in Budapest, Hungary, in April 2006, colocated with EvoCOP 2006. The 21 revised plenary papers and 11 revised poster papers were carefully reviewed and selected from 59 submissions. The papers address fundamental and theoretical issues, along with a wide variety of papers dealing with different application areas.

In this volume are the proceedings of the fourth European conference on - netic Programming (EuroGP 2001) which took place at Lake Como in Italy on April, 18{20 2001. EuroGP has become r mly established as the premier - ropean event devoted to Genetic Programming. EuroGP began life in 1998 as an international workshop and was held in Paris (14{15 April, LNCS 1391). - ter that it was held in Got .. eborg, Sweden (26{27 May 1999, LNCS 1598). Its r st appearance as a conference was last year in Edinburgh in Scotland (15{ 16 April, LNCS 1802). Each year EuroGP has been co-located with a series of specialist workshops (LNCS 1468, 1596, 1803). This year was no exception and EvoWorkshops 2001 were also held at Lake Como (18-19 April, LNCS 2037). Genetic Programming (GP) refers to a branch of Evolutionary Compu- tion in which computer programs are automatically generated over a period of time using a process that mimics Darwinian evolution. The 30 papers in these proceedings more than amply demonstrate the wide and varied applicability of GP.There are papers that apply GP to robotics, artic ial retina, character recognition, nancialprediction, digitall terandelectronic circuitdesign,image processing, data fusion, and biosequencing. In addition there are many papers that address foundational and theoretical issues. Arigorousdouble-blindrefereeing systemwasappliedtothe42submitted- pers. This resulted in 17 plenary talks(40% of those submitted) and 13 research posters.

Soft computing encompasses various computational methodologies, which, unlike conventional algorithms, are tolerant of imprecision, uncertainty, and partial truth. Soft computing technologies offer adaptability as a characteristic feature and thus permit the tracking of a problem through a changing environment. Besides some recent developments in areas like rough sets and probabilistic networks, fuzzy logic, evolutionary algorithms, and artificial neural networks are core ingredients of soft computing, which are all bio-inspired and can easily be combined synergetically.This book presents a well-balanced integration of fuzzy logic, evolutionary computing, and neural information processing. The three constituents are introduced to the reader systematically and brought together in differentiated combinations step by step. The text was developed from courses given by the authors and offers numerous illustrations as

This book constitutes the refereed proceedings of the 5th International Conference on Cellular Automata for Research and Industry, ACRI 2002, held in Geneva, Switzerland in October 2002. The 31 revised full papers presented together with 3 invited paper were carefully reviewed and selected from around 50 submissions. The topics covered range from theoretical issues to applications in various fields, including lattice gases, pattern recognition, cryptography, and authentication. Less known models receive attention as well, such as probabilistic, asynchronous, and multi-level automata. Among novel applications and models are highway traffic, population and growth dynamics, environmental applications, and collective intelligence.

Evolutionary computing, inspired by the biological world, is one of the emergent technologies of our time. Being essentially a software activity, it has been successfully applied, e.g. for optimization and machine learning in various areas. The tremendous increase in computational power and, more recently, the appearance of a new generation of programmable logic devices allow for a new approach to designing computing machines inspired by biological models: it is now possible to make the hardware itself evolve.This book is based on a workshop on evolvable hardware, held in Lausanne, Switzerland, in October 1995. It reports the state of the art of research in this field and presents two introductory chapters, written with the novice reader in mind.

Evolutionary algorithms (EAs) is now a mature problem-solving family of heuristics that has found its way into many important real-life problems and into leading-edge scientific research. Spatially structured EAs have different properties than standard, mixing EAs. By virtue of the structured disposition of the population members they bring about new dynamical features that can be harnessed to solve difficult problems faster and more efficiently. This book describes the state of the art in spatially structured EAs by using graph concepts as a unifying theme. The models, their analysis, and their empirical behavior are presented in detail. Moreover, there is new material on non-standard networked population structures such as small-world networks.The book should be of interest to advanced undergraduate and graduate students working in evolutionary computation, machine learning, and optimization. It should also be useful to researchers and professionals working in fields where the topological structures of populations and their evolution plays a role.

Soft computing encompasses various computational methodologies, which, unlike conventional algorithms, are tolerant of imprecision, uncertainty, and partial truth. Soft computing technologies offer adaptability as a characteristic feature and thus permit the tracking of a problem through a changing environment. Besides some recent developments in areas like rough sets and probabilistic networks, fuzzy logic, evolutionary algorithms, and artificial neural networks are core ingredients of soft computing, which are all bio-inspired and can easily be combined synergetically.This book presents a well-balanced integration of fuzzy logic, evolutionary computing, and neural information processing. The three constituents are introduced to the reader systematically and brought together in differentiated combinations step by step. The text was developed from courses given by the authors and offers numerous illustrations as

The book constitutes the refereed proceedings of the 11th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2013, held in Lausanne, Switzerland, in April 2013. The 51 revised full papers presented were carefully reviewed and selected from a total of 91 submissions. The papers are organized in topical sections on neural networks, evolutionary computation, soft computing, bioinformatics and computational biology, advanced computing, and applications.