Handbook on Computational Intelligence ·In 2 Volumes (Series on Computational Intelligence)

With the Internet, the proliferation of Big Data, and autonomous systems, mankind has entered into an era of 'digital obesity'. In this century, computational intelligence, such as thinking machines, have been brought forth to process complex human problems in a wide scope of areas — from social sciences, economics and biology, medicine and social networks, to cyber security.

The *Handbook of Computational Intelligence (in two volumes)* prompts readers to look at these problems from a non-traditional angle. It takes a step by step approach, supported by case studies, to explore the issues that have arisen in the process. The *Handbook* covers many classic paradigms, as well as recent achievements and future promising developments to solve some of these very complex problems. Volume one explores the subjects of fuzzy logic and systems, artificial neural networks, and learning systems. Volume two delves into evolutionary computation, hybrid systems, as well as the applications of computational intelligence in decision making, the process industry, robotics, and autonomous systems.

This work is a "one-stop-shop" for beginners, as well as an inspirational source for more advanced researchers. It is a useful resource for lecturers and learners alike.

**Contents:**

Introduction by the Editor

***Volume 1:* **

**Part I: Fuzzy Logic:**

Fundamentals of Fuzzy Set Theory *(Fernando Gomide)*

Granular Computing *(Andrzej Bargiela and Witold Pedrycz)*

Evolving Fuzzy Systems — Fundamentals, Reliability, Interpretability, Useability, Applications *(Edwin Lughofer)*

Modeling Fuzzy Rule-Based Systems (Rashmi Dutta Baruah and Diganta Baruah) **

Fuzzy Classifiers *(Hamid Bouchachia)*

Fuzzy Model-Based Control — Predictive and Adaptive Approach *(Igor Škrjanc and Saso Blažič)*

Fuzzy Fault Detection and Diagnosis *(Bruno Sielly Jales Costa)*

**Part II: Artificial Neural Networks and Learning Systems:**

The ANN and Learning Systems in Brains and Machines *(Leonid Perlovsky)*

Introduction to Cognitive Systems *(Péter Érdi and Mihály Bányai)*

A New View on Economics with Recurrent Neural Networks *(Hans-Georg Zimmermann, Ralph Grothmann and Christoph Tietz)*

Evolving Connectionist Systems for Adaptive Learning and Pattern Recognition: From Neuro-Fuzzy-, to Spiking- and Neurogenetic *(Nikola Kasabov)*

Reinforcement Learning with Applications in Automation Decision and Feedback Control *(Kyriakos G Vamvoudakis, Frank L Lewis and Draguna Vrabie)*

Kernel Models and Support Vector Machines *(Denis Kolev, Mikhail Suvorov and Dmitry Kangin)*

***Volume 2:* **

**Part III: Evolutionary Computation:**

History and Philosophy of Evolutionary Computation *(Carlos A Coello Coello, Carlos Segura and Gara Miranda)*

A Survey of Recent Works in Artificial Immune Systems (Guilherme Costa Silva and Dipankar Dasgupta)

Swarm Intelligence: An Introduction, History and Applications *(Fevrier Valdez)*

Memetic Algorithms *(Qiangfu Zhao, Yong Liu and Yan Pei)*

**Part IV: Hybrid Systems:**

Multi-objective Evolutionary Design of Fuzzy Rule-based Systems *(Michela Antonelli, Pietro Ducange and Francesco Marcelloni)*

Bio-Inspired Optimization of Interval Type-2 Fuzzy Controllers *(Oscar Castillo)*

Nature-Inspired Optimization of Fuzzy Controllers and Fuzzy Models *(Radu-Emil Precup and Radu-Codruţ David)*

Genetic Optimization of Modular Neural Networks for Pattern Recognition with a Granular Approach *(Patricia Melin)*

Hybrid Evolutionary-, Constructive- and Evolving Fuzzy Neur