Artificial Intelligence in Control and Decision-making Systems

This book presents an authoritative collection of contributions reporting on computational intelligence, fuzzy systems as well as artificial intelligence techniques for modelling, optimization, control and decision-making together with applications and case studies in engineering, management and economic sciences.Over the recent years, a considerable amount of research effort has been devoted to the development of advanced methods of artificial intelligence with a focus on its implementation in practice in different fields of human activity, especially for solving real control and decision-making problems in uncertainty.Dedicated to the Academician of the Polish Academy of Sciences, Professor Janusz Kacprzyk in recognition of his pioneering work, the book reports on theories, methods and new challenges in artificial intelligence, thus offering not only a timely reference guide but also a source of new ideas and inspirations for graduate students and researchers alike.The book consists of 18 chapters, presented by distinguished and experienced authors from 15 different countries (Australia, Brazil, Canada, Chile, Germany, Israel, Italy, PR China, R.N. Macedonia, Saudi Arabia, Spain, Turkey, USA, Ukraine and Vietnam). All chapters are grouped into three parts: (1) Computational Intelligence and Fuzzy Systems, (2) Artificial Intelligence Techniques in Modelling and Optimization and (3) Computational Intelligence in Control and Decision Support Processes.The book reflects recent developments and new directions in artificial intelligence, in particular, including computation method of the interval hull to solutions of interval and fuzzy interval linear systems, fuzzy Petri networks in supervisory control of Markov processes in robotic systems, fuzzy approaches for linguistic data summaries, first-approximation analysis for choosing fuzzy or neural systems and type-1 or type-2 fuzzy sets, matrix resolving functions in game dynamic problems, evolving stacking neuro-fuzzy probabilistic networks and their combined learning in online pattern recognition tasks, structural optimization of fuzzy control and decision-making systems, neural and granular fuzzy adaptive modelling, state and action abstraction for search and reinforcement learning algorithms.Among the most successful and perspective implementations in practical areas of human activity are algorithms for diagnosing neurological disorders, human-centric question-answering system, OWA operators in pensions, evaluation of the perception of public safety through fuzzy and multi-criteria approach, a multi-criteria hierarchical approach to investments, intelligent traffic signal control using the rule-based fuzzy system and generative adversarial networks in cybersecurity.The chapters provide an easy-to-follow introduction to the topics that are addressed, including the most relevant references, so that anyone interested in them can start their introduction to the topic through these references. At the same time, all of them correspond to different aspects of work-in-progress being carried out in various research groups throughout the world and, therefore, provide information on the state-of-the-art of these topics.This book is useful for researchers and students who are interested in artificial intelligence and in advanced control and decision-making systems.