Nature Inspired Cooperative Strategies for Optimization (NICSO 2007)

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Natalio Krasnogor, Vincenzo Nicosia, Mario Pavone, David Alejandro Pelta
Springer Science & Business Media, May 14, 2008 - Computers - 520 pages

Biological and natural processes have been a continuous source of inspiration for the sciences and engineering. For instance, the work of Wiener in cybernetics was influenced by feedback control processes observable in biological systems; McCulloch and Pitts description of the artificial neuron was instigated by biological observations of neural mechanisms; the idea of survival of the fittest inspired the field of evolutionary algorithms and similarly, artificial immune systems, ant colony optimisation, automated self-assembling programming, membrane computing, etc. also have their roots in natural phenomena.

The second International Workshop on Nature Inspired Cooperative Strategies for Optimization (NICSO), was held in Acireale, Italy, during November 8-10, 2007. The aim for NICSO 2007 was to provide a forum were the latest ideas and state of the art research related to cooperative strategies for problem solving arising from Nature could be discussed. The contributions collected in this book were strictly peer reviewed by at least three members of the international programme committee, to whom we are indebted for their support and assistance. The topics covered by the contributions include several well established nature inspired techniques like Genetic Algorithms, Ant Colonies, Artificial Immune Systems, Evolutionary Robotics, Evolvable Systems, Membrane Computing, Quantum Computing, Software Self Assembly, Swarm Intelligence, etc.

From inside the book

Contents

Optimization
14
Introduction
15
Flockingbased Document Clustering on the Graphics Processing Unit
27
Artificial Immune System for Collaborative Spam Filtering
39
MP Systems and Hybrid Petri Nets 53
52
Spatial Sorting of Binary Metadata Documents via NatureInspired
63
hCHAC4 an ACO Algorithm for Solving the FourCriteria Military
73
E MezuraMontes
84
A New Nature Inspired Computational
221
Social Impact based Approach to Feature Subset Selection Martin Macaš Lenka Lhotska and Vaclav Kremen
239
Influence of Different Deviations Allowed for Equality Constraints
249
Learning Classifier System with Selfadaptive Discovery Mechanism
273
Learning Robust Dynamic Networks in Prokaryotes
299
Discrete Particle Swarm Optimization for the Minimum Labelling
312
A Surface Tension and Coalescence Model for Dynamic Distributed
335
A Hybrid Genetic Algorithm for the Travelling Salesman Problem
357

Searching Ground States of Ising Spin Glasses with Genetic Algorithms
85
Andrei Bautu and Elena Bautu
95
A New EvolutionarySwarm Cooperative Algorithm
105
An Adaptive Metaheuristic for the Simultaneous Resolution
125
Honey Bees Mating Optimization Algorithm for the Vehicle
138
Dynamic Adaptation of Genetic Operators Probabilities
159
Comparing the Neural and Immune
179
Memetic Algorithm for the Generalized Asymmetric Traveling Salesman
199
Gemma BelEnguix and M Dolores JimenezLopez
379
Implementation of Massive Parallel Networks of Evolutionary
399
A Genetic Algorithm Framework Applied to Quantum
419
Thomas Sierocinski Antony Le Bechec Nathalie Theret and Dimitri Petritis
443
Automatic Selection for the Beta Basis Function Neural Networks Habib Dhahri and Adel Alimi
461
A Problem of Generalization Which Works
475
A Genetic Algorithm Based on Complex Networks Theory
495
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Biological and natural processes have been a continuous source of inspiration for the sciences and engineering. For instance, the work of Wiener in cybernetics was influenced by feedback control processes observable in biological systems; McCulloch and Pitts description of the artificial neuron was instigated by biological observations of neural mechanisms; the idea of survival of the fittest inspired the field of evolutionary algorithms and similarly, artificial immune systems, ant colony optimisation, automated self-assembling programming, membrane computing, etc. also have their roots in natural phenomena.

The second International Workshop on Nature Inspired Cooperative Strategies for Optimization (NICSO), was held in Acireale, Italy, during November 8-10, 2007. The aim for NICSO 2007 was to provide a forum were the latest ideas and state of the art research related to cooperative strategies for problem solving arising from Nature could be discussed. The contributions collected in this book were strictly peer reviewed by at least three members of the international programme committee, to whom we are indebted for their support and assistance. The topics covered by the contributions include several well established nature inspired techniques like Genetic Algorithms, Ant Colonies, Artificial Immune Systems, Evolutionary Robotics, Evolvable Systems, Membrane Computing, Quantum Computing, Software Self Assembly, Swarm Intelligence, etc.

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