Xin Yao

Peter Tino

Jim Smith

Edmund Burke

Hans-Paul Schwefel

Jose A. Lozano

Juan J. Merelo-Guervós

John A. Bullinaria

Jonathan Rowe

Ata Kabán

We are very pleased to present this LNCS volume, the proceedings of the 8th InternationalConferenceonParallelProblemSolvingfromNature(PPSNVIII). PPSN is one of the most respected and highly regarded conference series in evolutionary computation and natural computing/computation. This biennial eventwas?rstheldinDortmundin1990,andtheninBrussels(1992),Jerusalem (1994), Berlin (1996), Amsterdam (1998), Paris (2000), and Granada (2002). PPSN VIII continues to be the conference of choice by researchers all over the world who value its high quality. We received a record 358 paper submissions this year. After an extensive peer review process involving more than 1100 reviews, the programme c- mittee selected the top 119 papers for inclusion in this volume and, of course, for presentation at the conference. This represents an acceptance rate of 33%. Please note that review reports with scores only but no textual comments were not considered in the chairs’ ranking decisions. The papers included in this volume cover a wide range of topics, from e- lutionary computation to swarm intelligence and from bio-inspired computing to real-world applications. They represent some of the latest and best research in evolutionary and natural computation. Following the PPSN tradition, all - persatPPSNVIII werepresentedasposters.Therewere7 sessions:eachsession consisting of around 17 papers. For each session, we covered as wide a range of topics as possible so that participants with di?erent interests would ?nd some relevant papers at every session.

8th International Conference, Birmingham, UK, September 18-22, 2004, Proceedings

Parallel Problem Solving from Nature - PPSN VIII

Hans-Georg Beyer

Thomas Philip Runarsson

L. Darrell Whitley

This book constitutes the refereed proceedings of the 9th International Conference on Parallel Problem Solving from Nature, PPSN 2006. The book presents 106 revised full papers covering a wide range of topics, from evolutionary computation to swarm intelligence and bio-inspired computing to real-world applications. These are organized in topical sections on theory, new algorithms, applications, multi-objective optimization, evolutionary learning, as well as representations, operators, and empirical evaluation.

9th International Conference, Reykjavik, Iceland, September 9-13, 2006, Proceedings

Parallel Problem Solving from Nature - PPSN IX

Hujun Yin

Yang Gao

Minho Lee

Thomas Weise

Bin Li

Ke Tang

Frank Klawonn

This book constitutes the refereed proceedings of the 14th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2013, held in Hefei, China, in October 2013. The 76 revised full papers presented were carefully reviewed and selected from more than 130 submissions. These papers provided a valuable collection of latest research outcomes in data engineering and automated learning, from methodologies, frameworks and techniques to applications. In addition to various topics such as evolutionary algorithms, neural networks, probabilistic modelling, swarm intelligent, multi-objective optimisation, and practical applications in regression, classification, clustering, biological data processing, text processing, video analysis, including a number of special sessions on emerging topics such as adaptation and learning multi-agent systems, big data, swarm intelligence and data mining, and combining learning and optimisation in intelligent data engineering.

14th International Conference, IDEAL 2013, Hefei, China, October 20-23, 2013, Proceedings

Intelligent Data Engineering and Automated Learning -- IDEAL 2013

Kalyanmoy Deb

Günther Rudolph

Juan Julian Merelo

Evelyne Lutton

Marc Schoenauer

We are proud to introduce the proceedings of the Sixth International Conference on Parallel Problem Solving from Nature, PPSN VI, held in Paris, Prance, on 18-20 September 2000. PPSN VI was organized in association with the Genetic and Evolutionary Computing Conference (GECCO'2000) and the Congress on Evolutionary Computation (CEC'2000), reflecting the beneficial interaction between the conference activities in Europe and in the USA in the field of natural computation. Starting in 1990 in Dortmund, Germany (Proceedings, LNCS vol. 496, Sprin ger, 1991), this biannual meeting has been held in Brussels, Belgium (Procee dings, Elsevier, 1992), Jerusalem, Israel (Proceedings, LNCS vol. 866, Springer, 1994), Berlin, Germany (Proceedings, LNCS vol. 1141, Springer, 1996), and Amsterdam, The Netherlands (Proceedings, LNCS vol. 1498, Springer, 1998), where it was decided that Paris would be the location of the 2000 conference with Marc Schoenauer as the general chair. The scientific content of the PPSN conference focuses on problem solving pa radigms gleaned from a natural models. Characteristic for Natural Computing is the metaphorical use of concepts, principles and mechanisms underlying natural systems, such as evolutionary processes involving mutation, recombination, and selection in natural evolution, annealing or punctuated equilibrium processes of many-particle systems in physics, growth processes in nature and economics, collective intelligence in biology, DNA-based computing in molecular chemistry, and multi-cellular behavioral processes in neural and immune networks.

6th International Conference, Paris, France, September 18-20 2000 Proceedings

Parallel Problem Solving from Nature-PPSN VI

Graham Kendall

Siang Yew Chong

In 1984, Robert Axelrod published a book, relating the story of two competitions which he ran, where invited academics entered strategies for the Iterated Prisoners' Dilemma. The book, almost 20 years on, is still widely read and cited by academics and the general public.As a celebration of that landmark work, we have recreated those competitions to celebrate its 20th anniversary, by again inviting academics to submit prisoners' dilemma strategies. The first of these new competitions was run in July 2004, and the second in April 2005. Iterated Prisoners' Dilemma: 20 Years On essentially provides an update of the Axelrod's book.Specifically, it ? Presents the prisoners' dilemma, its history and variants ? Highlights original Axelrod's work and its impact ? Discusses results of new competitions ? Showcases selected papers that reflect the latest researches in the area

20 Years on

The Iterated Prisoners' Dilemma

Bernhard Rinner

Peter R. Lewis

Marco Platzner

Jim Tørresen

Taking inspiration from self-awareness in humans, this book introduces the new notion of computational self-awareness as a fundamental concept for designing and operating computing systems. The basic ability of such self-aware computing systems is to collect information about their state and progress, learning and maintaining models containing knowledge that enables them to reason about their behaviour. Self-aware computing systems will have the ability to utilise this knowledge to effectively and autonomously adapt and explain their behaviour, in changing conditions. This book addresses these fundamental concepts from an engineering perspective, aiming at developing primitives for building systems and applications. It will be of value to researchers, professionals and graduate students in computer science and engineering.

An Engineering Approach

Self-aware Computing Systems

Ruhul Sarker

Masoud Mohammadian

The use of evolutionary computation techniques has grown considerably over the past several years. Over this time, the use and applications of these techniques have been further enhanced resulting in a set of computational intelligence (also known as modern heuristics) tools that are particularly adept for solving complex optimization problems. Moreover, they are characteristically more robust than traditional methods based on formal logics or mathematical programming for many real world OR/MS problems. Hence, evolutionary computation techniques have dealt with complex optimization problems better than traditional optimization techniques although they can be applied to easy and simple problems where conventional techniques work well. Clearly there is a need for a volume that both reviews state-of-the-art evolutionary computation techniques, and surveys the most recent developments in their use for solving complex OR/MS problems. This volume on Evolutionary Optimization seeks to fill this need. Evolutionary Optimization is a volume of invited papers written by leading researchers in the field. All papers were peer reviewed by at least two recognized reviewers. The book covers the foundation as well as the practical side of evolutionary optimization.

Evolutionary Optimization

Evolutionary computation is the study of computational systems which use ideas and get inspiration from natural evolution and adaptation. This book is devoted to the theory and application of evolutionary computation. It is a self-contained volume which covers both introductory material and selected advanced topics. The book can roughly be divided into two major parts: the introductory one and the one on selected advanced topics. Each part consists of several chapters which present an in-depth discussion of selected topics. A strong connection is established between evolutionary algorithms and traditional search algorithms. This connection enables us to incorporate ideas in more established fields into evolutionary algorithms. The book is aimed at a wide range of readers. It does not require previous exposure to the field since introductory material is included. It will be of interest to anyone who is interested in adaptive optimization and learning. People in computer science, artificial intelligence, operations research, and various engineering fields will find it particularly interesting. Contents:Introduction (X Yao)Evolutionary Computation in Behavior Engineering (M Colombetti & M Dorigo)A General Method for Incremental Self-Improvement and Multi-Agent Learning (J Schmidhuber)Teacher: A Genetics-Based System for Learning and for Generalizing Heuristics (B W Wah & A Ieumwananonthachai)Automatic Discovery of Protein Motifs Using Genetic Programming (J R Koza & D Andre)The Role of Self Organization in Evolutionary Computations (A C Tsoi & J Shaw)Virus-Evolutionary Genetic Algorithm and Its Application to Traveling Salesman Problem (T Fukuda et al.)Hybrid Evolutionary Optimization Algorithm for Constrained Problems (J-H Kim & H Myung)CAM-BRAIN — The Evolutionary Engineering of a Billion Neuron Artificial Brain (H de Garis)An Evolutionary Approach to the N-Player Iterated Prisoner's Dilemma Game (X Yao & Darwen) Readership: Graduate students, practitioners and researchers in engineering and electronics and computer science. keywords:Genetic Algorithms;Evolutionary Computation;Evolutionary Algorithms;Genetic Programming;Evolutionary Robotics;Global Optimization;Evolutionary Games;Global Optimization;Machine Learning;Artificial Intelligence

Evolutionary Computation: Theory and Applications

Will Byrne

Emilio Corchado

This book constitutes the refereed proceedings of the 8th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2007, held in Birmingham, UK, in December 2007. The 170 revised full papers presented were carefully reviewed and selected from more than 270 submissions. The papers are organized in topical sections on learning and information processing, data mining and information management, bioinformatics and neuroinformatics, agents and distributed systems, financial engineering and modeling, agent-based approach to service sciences, as well as neural-evolutionary fusion algorithms and their applications.

8th International Conference, Birmingham, UK, December 16-19, 2007, Proceedings

Intelligent Data Engineering and Automated Learning - IDEAL 2007

Xin Yao

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