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Nature Inspired Cooperative Strategies for Optimization (NICSO 2007) de Natalio Krasnogor

Nature Inspired Cooperative Strategies for Optimization (NICSO 2007): Studies in Computational Intelligence, cartea 129

Editat de Natalio Krasnogor, Vincenzo Nicosia, Mario Pavone, David Alejandro Pelta
en Limba Engleză Hardback – 14 mai 2008
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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Specificații

ISBN-13: 9783540789864
ISBN-10: 3540789863
Pagini: 501
Ilustrații: XIV, 520 p.
Dimensiuni: 155 x 235 x 33 mm
Greutate: 0.92 kg
Ediția:2008
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Studies in Computational Intelligence

Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

A Preliminary Study of Fitness Inheritance in Evolutionary Constrained Optimization.- Probabilistically Guided Prefix Gene Expression Programming.- Flocking-based Document Clustering on the Graphics Processing Unit.- Artificial Immune System for Collaborative Spam Filtering.- MP Systems and Hybrid Petri Nets.- Spatial Sorting of Binary Metadata Documents via Nature-Inspired Agents in Grids.- hCHAC-4, an ACO Algorithm for Solving the Four-Criteria Military Path-finding Problem.- Searching Ground States of Ising Spin Glasses with Genetic Algorithms and Binary Particle Swarm Optimization.- A Hybrid System of Nature Inspired Metaheuristics.- ESCA: A New Evolutionary-Swarm Cooperative Algorithm.- Stabilizing Swarm Intelligence Search via Positive Feedback Resource Allocation.- An Adaptive Metaheuristic for the Simultaneous Resolution of a Set of Instances.- Honey Bees Mating Optimization Algorithm for the Vehicle Routing Problem.- Self-Organization on Silicon: System Integration of a Fixed-Point Swarm Coprocessor.- Dynamic Adaptation of Genetic Operators’ Probabilities.- Cooperative Co-evolution Inspired Operators for Classical GP Schemes.- Biologically Inspired Clustering: Comparing the Neural and Immune Paradigms.- CODEA: An Architecture for Designing Nature-inspired Cooperative Decentralized Heuristics.- Memetic Algorithm for the Generalized Asymmetric Traveling Salesman Problem.- Particle Swarm Based Collective Searching Model for Adaptive Environment.- Central Force Optimization: A New Nature Inspired Computational Framework for Multidimensional Search and Optimization.- Social Impact based Approach to Feature Subset Selection.- Influence of Different Deviations Allowed for Equality Constraints on Particle Swarm Optimization and Differential Evolution.- Efficiency ofVarious Stochastic Optimization Algorithms in High Frequency Electromagnetic Applications.- Learning Classifier System with Self-adaptive Discovery Mechanism.- An Approach to Genome Statistics Inspired by Stochastic or Quantum Models of Computing: A Survey.- Learning Robust Dynamic Networks in Prokaryotes by Gene Expression Networks Iterative Explorer (GENIE).- Discrete Particle Swarm Optimization for the Minimum Labelling Steiner Tree Problem.- Ant Colony Cooperative Strategy in Electrocardiogram and Electroencephalogram Data Clustering.- A Surface Tension and Coalescence Model for Dynamic Distributed Resources Allocation in Massively Parallel Processors on-Chip.- Cooperative Learning Sensitive Agent System for Combinatorial Optimization.- A Hybrid Genetic Algorithm for the Travelling Salesman Problem.- A BioInspired Model for Parsing of Natural Languages.- An Evolutionary Approach for Performing Structural Unit-Testing on Third-Party Object-Oriented Java Software.- Adaptive Spatial Allocation of Resource for Parallel Genetic Algorithm.- Implementation of Massive Parallel Networks of Evolutionary Processors (MPNEP): 3-Colorability Problem.- Multi-Constraints Routing Algorithm Based on Swarm Intelligence over High Altitude Platforms.- A Genetic Algorithm Framework Applied to Quantum Circuit Synthesis.- Semantic Distillation: A Method for Clustering Objects by their Contextual Specificity.- UPlanIT: An Evolutionary Based Production Planning and Scheduling System.- Performance Analysis of Turning Process via Particle Swarm Optimization.- Automatic Selection for the Beta Basis Function Neural Networks.- Evolvable Hardware: A Problem of Generalization Which Works Best: Large Population Size and Small Number of Generations or visa versa?.- Detecting Hierarchical Organization in Complex Networks by Nearest Neighbor Correlation.- A Genetic Algorithm Based on Complex Networks Theory for the Management of Airline Route Networks.- GAHC: Improved Genetic Algorithm.

Notă biografică

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.

Caracteristici

Presents latest results in Nature Inspired Cooperative Strategies for Optimization