Computational Intelligence -

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Résumé :
Computational Intelligence: A Compendium presents a well structured overview about this rapidly growing field with contributions of leading experts in Computational Intelligence. The main focus of the compendium is on applied methods tired-and-proven effective to realworld problems, which is especially useful for practitioners, researchers, students and also newcomers to the field. The 25 chapters are grouped into the following themes: I. Overview and Background II. Data Preprocessing and Systems Integration III. Artificial Intelligence IV. Logic and Reasoning V. Ontology VI. Agents VII. Fuzzy Systems VIII. Artificial Neural Networks IX. Evolutionary Approaches X. DNA and Immune-based Computing.

Sommaire:
Overview, Background.- Computational Intelligence: An Introduction.- Preprocessing, Visualization, Systems Integration.- Data Reduction for Pattern Recognition and Data Analysis.- Topographic Maps for Clustering and Data Visualization.- Complex Systems Paradigms for Integrating Intelligent Systems: A Game Theoretic Approach.- Artificial Intelligence.- Emotional Intelligence: Giving Computers Effective Emotional Skills to Aid Interaction.- Logic and Reasoning.- The Paraconsistent Annotated Logic Program EVALPSN and its Application.- The Data-Oriented Parsing Approach: Theory and Application.- Ontology.- Graph-Based Representation and Reasoning for Ontologies.- An Ontology-Based Intelligent Mobile System for Tourist Guidance.- Intelligent Agents.- Open Source Agent-Based Modeling Frameworks.- Agent-Based Grid Computing.- Decentralized Multi-Agent Clustering in Scale-free Sensor Networks.- Computational Intelligence in Agent-Based Computational Economics.- Fuzzy Systems.- Semantics and Perception of Fuzzy Sets and Fuzzy Mappings.- Evolutionary Multiobjective Design of Fuzzy Rule-Based Classifiers.- Artificial Neural Networks.- Data Mining in QoS-Aware Media Grids.- The Self-Organizing Maps: Background, Theories, Extensions and Applications.- Neural Systems Engineering.- Artificial Brains: An Evolved Neural Net Module Approach.- Evolutionary Approaches.- Evolving Artificial Neural Network Ensembles.- An Order Based Memetic Evolutionary Algorithm for Set Partitioning Problems.- Genetic Programming: An Introduction and Tutorial, with a Survey of Techniques and Applications.- The Particle Swarm Algorithm.- DNA and Immunity-Based Computing.- DNA Computing and its Application.- The Next Generation of Immunity-Based Systems: From Specific Recognition to Computational Intelligence.

From the reviews: This compendium contains an excellent summary of the past, present, and future of the field of artificial intelligence or machine learning, now more appropriately named as computational intelligence. ...This compendium is particularly valuable not only for its thorough coverage, but also for the numerous resources provided with every chapter ... . This material gives the reader an excellent foundation for further study, making this a valuable reference for those in the area. Summing Up: Highly recommended. Graduate, research, faculty, and professional collections. (J. Y. Cheung, Choice, Vol. 46 (6), February, 2009) Computational intelligence (CI) was in real need of this compendium, as it is an exhaustive summary that explores the theory of intelligence, through possible computational means. ... This compendium is essential reading for researchers with an interest in the field; it could also serve as a resource for a doctoral thesis or various research projects, as it refers to literature that covers every aspect of the field and provides promising solutions to CI open problems. (Mario Aoun, ACM Computing Reviews, May, 2009)