Computational Intelligence: Collaboration, Fusion and Emergence

Christine L. Mumford (auth.), Christine L. Mumford, Lakhmi C. Jain (eds.)9783642017988, 3642017983

This book is the first in a new series entitled “Intelligent Systems Reference Library”. It is a collection of chapters written by leading experts, covering a rich and diverse variety of computer-based techniques, all involving some aspect of computational intelligence (CI). Authors in this collection recognize the limitations of individual paradigms, and propose some practical and novel ways in which different CI techniques can be combined with each other, or with more traditional computational techniques, to produce powerful problem-solving environments.

Common themes to be found in the various chapters of this collection include the following:

Fusion,

Collaboration, and

Emergence.

Fusion describes the hybridization of two or more techniques, at least one of which will involve CI. Collaboration ensures that the different techniques work effectively together. Finally, Emergence refers to the phenomenon that complex behaviour can arise as a result of collaboration between simple processing elements.

The book covers a wide range of cutting edge techniques and applications, and is divided into the following parts:

I. Introduction

II. Fusing evolutionary algorithms and fuzzy logic

III. Adaptive solution schemes

IV. Multi-agent systems

V. Computer vision

VI. Communication for CI systems

VII. Artificial immune systems

VIII. Parallel evolutionary algorithms

IX. CI for clustering and classification

Table of contents :
Front Matter….Pages –
Front Matter….Pages 1-1
Synergy in Computational Intelligence….Pages 3-21
Computational Intelligence: The Legacy of Alan Turing and John von Neumann….Pages 23-43
Front Matter….Pages 45-45
Multiobjective Evolutionary Algorithms for Electric Power Dispatch Problem….Pages 47-82
Fuzzy Evolutionary Algorithms and Genetic Fuzzy Systems: A Positive Collaboration between Evolutionary Algorithms and Fuzzy Systems….Pages 83-130
Multiobjective Genetic Fuzzy Systems….Pages 131-173
Front Matter….Pages 175-175
Exploring Hyper-heuristic Methodologies with Genetic Programming….Pages 177-201
Adaptive Constraint Satisfaction: The Quickest First Principle….Pages 203-230
Front Matter….Pages 231-231
Collaborative Computational Intelligence in Economics….Pages 233-273
IMMUNE: A Collaborating Environment for Complex System Design….Pages 275-320
Bayesian Learning for Cooperation in Multi-Agent Systems….Pages 321-360
Collaborative Agents for Complex Problems Solving….Pages 361-399
Front Matter….Pages 401-401
Predicting Trait Impressions of Faces Using Classifier Ensembles….Pages 403-439
The Analysis of Crowd Dynamics: From Observations to Modelling….Pages 441-472
Front Matter….Pages 473-473
Computational Intelligence for the Collaborative Identification of Distributed Systems….Pages 475-500
Collaboration at the Basis of Sharing Focused Information: The Opportunistic Networks….Pages 501-524
Front Matter….Pages 525-525
Exploiting Collaborations in the Immune System: The Future of Artificial Immune Systems….Pages 527-558
Front Matter….Pages 559-559
Evolutionary Computation: Centralized, Parallel or Collaborative….Pages 561-595
Front Matter….Pages 597-597
Fuzzy Clustering of Likelihood Curves for Finding Interesting Patterns in Expression Profiles….Pages 599-622
A Hybrid Rule-Induction/Likelihood-Ratio Based Approach for Predicting Protein-Protein Interactions….Pages 623-637
Improvements in Flock-Based Collaborative Clustering Algorithms….Pages 639-672
Front Matter….Pages 597-597
Combining Statistics and Case-Based Reasoning for Medical Research….Pages 673-696
Collaborative and Experience-Consistent Schemes of System Modelling in Computational Intelligence….Pages 697-723
Back Matter….Pages –