Overview

The last few decades have seen a new era of artificial intelligence focusing on emulating humans, either in their behaviour or in their neurophysiology. Computational intelligence is a well-established paradigm, where new theories with a sound biological understanding have been evolving. This volume is a rare collection of 12 chapters compiling the latest state-of-the-art research in the area of intelligent paradigms authored by the world leading well-established experts in the field. Each chapter focuses on different aspects of intelligent systems. The chapters present the latest theoretical developments as well as practical applications of these latest technologies.

Full Product Details

Author:   Ajith Abraham ,  Prof. Lakhmi C. Jain ,  Janusz Kacprzyk
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Physica-Verlag GmbH & Co
Edition:   Softcover reprint of hardcover 1st ed. 2003
Volume:   113
Dimensions:   Width: 15.50cm , Height: 1.50cm , Length: 23.50cm
Weight:   0.450kg
ISBN:  

9783790825213

ISBN 10:   3790825212
Pages:   272
Publication Date:   21 October 2010
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

1. Intelligent systems: architectures and perspectives.- 2. Hybrid architecture for autonomous robots, based on representations, perception and intelligent control.- 3. An intuitionistic fuzzy set based approach to intelligent data analysis: an application to medical diagnosis.- 4. A fuzzy inference methodology based on the fuzzification of set inclusion.- 5. A fuzzy approach to job-shop scheduling problem based on imprecise processing times.- 6. On efficient representation of expert knowledge by fuzzy logic.- 7. Discovering efficient learning rules for feedforward neural networks using genetic programming.- 8. Neuro-fuzzy methods for modeling and identification.- 9. Constrained two dimensional bin packing using a genetic algorithm.- 10. Sequential and distributed evolutionary algorithms for combinatorial optimization problems.- 11. Embodied emotional agent in intelligent training system.- 12. Optimizing intelligent agent’s constraint satisfaction with neural networks.

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