Soft computing is a consortium of computing methodologies that provide a foundation for the conception, design, and deployment of intelligent systems and aims to formalize the human ability to make rational decisions in an environment of uncertainty and imprecision.

1 Computational Intelligence.- Roles of Soft Computing and Fuzzy Logic in the Conception, Design and Deployment of Information/Intelligent Systems.- Computational Intelligence Defined — By Everyone!.- Computational Intelligence: Extended Truth Tables and Fuzzy Normal Forms.- Uncertainty Theories by Modal Logic.- 2 Foundations of Fuzzy Theory.- Sup-T Equations: State of the Art.- Measures of Specificity.- What’s in a Fuzzy Membership Value?.- New Types of Generalized Operations.- 3 Fuzzy Systems.- Intelligent Fuzzy System Modeling.- Fuzzy Inference Systems: A Critical Review.- Fuzzy Decision Support Systems.- Neuro-Fuzzy Systems.- Fuzzified Petri-Nets and Their Application to Organising Supervisory Controller.- 4 Neural Networks.- A Review of Neural Networks with Direct Learning Based on Linear or Non—linear Threshold Logics.- The Morphogenetic Neuron.- Boolean Soft Computing by Non—linear Neural Networks with Hyperincursive Stack Memory.- 5 Data Analysis.- Using Competitive Learning Models for Multiple Prototype Classifier Design.- Fuzzy Data Analysis.- Probabilistic and Possibilistic Networks and How To Learn Them from Data.- 6 Applications.- Image Pattern Recognition Based on Fuzzy Technology.- Fuzzy Sets and the Management of Uncertainty in Computer Vision.- Intelligent Robotic Systems Based on Soft Computing—Adaptation, Learning and Evolution.- Hardware and Software Architectures for Soft Computing.- Fuzzy Logic Control for Design and Control of Manufacturing Systems.- Applications of Intelligent Multiobjective Fuzzy Decision Making.- A Product Life Cycle Information Management System Infrastructure with CAD/CAE/CAM, Task Automation, and Intelligent Support Capabilities.