The editors describe in this book, new methods for evolutionary design of intelligent systems using soft computing and their applications in modeling, simulation and control. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and evolutionary algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in four main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of evolutionary design of fuzzy systems in intelligent control, which consists of papers that propose new methods for designing and optimizing intelligent controllers for different applications. The second part contains papers with the main theme of evolutionary design of intelligent systems for pattern recognition applications, which are basically papers using evolutionary algorithms for optimizing modular neural networks with fuzzy systems for response integration, for achieving pattern recognition in different applications. The third part contains papers with the themes of models for learning and social simulation, which are papers that apply intelligent systems to the problems of designing learning objects and social agents. The fourth part contains papers that deal with intelligent systems in robotics applications and hardware implementations.
Author(s): Ricardo Martínez-Marroquín, Oscar Castillo, José Soria (auth.), Oscar Castillo, Witold Pedrycz, Janusz Kacprzyk (eds.)
Series: Studies in Computational Intelligence 257
Edition: 1
Publisher: Springer-Verlag Berlin Heidelberg
Year: 2009
Language: English
Pages: 327
Tags: Appl.Mathematics/Computational Methods of Engineering; Artificial Intelligence (incl. Robotics)
Front Matter....Pages -
Front Matter....Pages 1-1
Optimization of Membership Functions of a Fuzzy Logic Controller for an Autonomous Wheeled Mobile Robot Using Ant Colony Optimization....Pages 3-16
Evolutionary Optimization of Type-2 Fuzzy Logic Systems Applied to Linear Plants....Pages 17-31
Multi-Agent System with Fuzzy Logic Control for Autonomous Mobile Robots in Known Environments....Pages 33-52
Hybrid Interval Type-1 Non-singleton Type-2 Fuzzy Logic Systems Are Type-2 Adaptive Neuro-fuzzy Inference Systems....Pages 53-61
Centralized Direct and Indirect Neural Control of Distributed Parameter Systems....Pages 63-81
Front Matter....Pages 83-83
An Ensemble Neural Network Architecture with Fuzzy Response Integration for Complex Time Series Prediction....Pages 85-110
Optimization of Fuzzy Response Integrators in Modular Neural Networks with Hierarchical Genetic Algorithms: The Case of Face, Fingerprint and Voice Recognition....Pages 111-129
Modular Neural Network with Fuzzy Integration of Responses for Face Recognition....Pages 131-158
A Modular Neural Network with Fuzzy Response Integration for Person Identification Using Biometric Measures....Pages 159-183
Signature Recognition with a Hybrid Approach Combining Modular Neural Networks and Fuzzy Logic for Response Integration....Pages 185-201
Front Matter....Pages 203-203
A Hybrid Recommender System Architecture for Learning Objects....Pages 205-211
TA-Fuzzy Semantic Networks for Interaction Representation in Social Simulation....Pages 213-225
Fuzzy Personality Model Based on Transactional Analysis and VSM for Socially Intelligent Agents and Robots....Pages 227-241
Front Matter....Pages 243-243
Controlling Unstable Non-Minimum-Phase Systems with Fuzzy Logic: The Perturbed Case....Pages 245-257
Genetic Optimization for the Design of Walking Patterns of a Biped Robot....Pages 259-271
Design and Simulation of the Type-2 Fuzzification Stage: Using Active Membership Functions....Pages 273-293
Methodology to Test and Validate a VHDL Inference Engine of a Type-2 FIS, through the Xilinx System Generator....Pages 295-308
Modeling and Simulation of the Defuzzification Stage of a Type-2 Fuzzy Controller Using the Xilinx System Generator and Simulink....Pages 309-325
Back Matter....Pages -
