Traditional artificial intelligence (AI) techniques are based around mathematical techniques of symbolic logic, with programming in languages such as Prolog and LISP invented in the 1960s. These are referred to as "crisp" techniques by the soft computing community. The new wave of AI methods seeks inspiration from the world of biology, and is being used to create numerous real-world intelligent systems with the aid of soft computing tools. These new methods are being increasingly taught at the upper end of the curriculum, sometimes as an adjunct to traditional AI courses, and sometimes as a replacement for them. Where a more radical approach is taken and the course is being taught at an introductory level, we have recently published Negnevitsky's book. Karray and Silva will be suitable for the majority of courses which will be found at an advanced level. Karray and de Silva cover the problem of control and intelligent systems design using soft-computing techniques in an integrated manner. They present both theory and applications, including industrial applications, and the book contains numerous worked examples, problems and case studies. Covering the state-of-the-art in soft-computing techniques, the book gives the reader sufficient knowledge to tackle a wide range of complex systems for which traditional techniques are inadequate.

This book presents high-quality research papers presented at the International Conference on Soft Computing for Intelligent Systems (SCIS 2020), held during 18–20 December 2020 at University Institute of Engineering and Technology, Kurukshetra University, Kurukshetra, Haryana, India. The book encompasses all branches of artificial intelligence, computational sciences and machine learning which is based on computation at some level such as AI-based Internet of things, sensor networks, robotics, intelligent diabetic retinopathy, intelligent cancer genes analysis using computer vision, evolutionary algorithms, fuzzy systems, medical automatic identification intelligence system and applications in agriculture, health care, smart grid and instrumentation systems. The book is helpful for educators, researchers and developers working in the area of recent advances and upcoming technologies utilizing computational sciences in signal processing, imaging, computing, instrumentation, artificial intelligence and their applications.

Annotation Intelligent Systems cover a broad area of knowledge-based systems, computational intelligence, soft computing, and their hybrid combinations. Research and development in intelligent systems have enabled us to not only solve a range of problems which were previously considered too difficult but also have enabled a larger number of other problems to be tacked more effectively. This volume focuses on the recent research developments on intelligent systems in a hybrid environment and its applications in image processing, internet modelling and data mining. The different contributions presented in this volume were accepted for the Second International Conference on Hybrid Intelligent Systems (HIS'02).

The proceedings of the Third International Conference on Intelligent Systems Design and Applications (ISDA 2003) held in Tulsa, USA, August 10-13. Current research in all areas of computational intelligence is presented including design of artificial neural networks, fuzzy systems, evolutionary algorithms, hybrid computing systems, intelligent agents, and their applications in science, technology, business and commerce. Main themes addressed by the conference are the architectures of intelligent systems, image, speech and signal processing, internet modeling, data mining, business and management applications, control and automation, software agents and knowledge management.

Artificial intelligence has, traditionally focused on solving human-centered problems like natural language processing or common-sense reasoning. On the other hand, for a while now soft computing has been applied successfully in areas like pattern recognition, clustering, or automatic control. The papers in this book explore the possibility of bringing these two areas together. This book is unique in the way it concentrates on building intelligent software systems by combining methods from diverse disciplines, such as fuzzy set theory, neuroscience, agent technology, knowledge discovery, and symbolic artificial intelligence. The first part of the book focuses on foundational aspects and future directions; the second part provides the reader with an overview of recently developed software tools for building flexible intelligent systems; the final section studies developed applications in various fields.

This book comprises a selection of papers on new methods for analysis and design of hybrid intelligent systems using soft computing techniques from the IFSA 2007 World Congress, held in Cancun, Mexico, June 2007.