Computational intelligence is a well-established paradigm, where new theories with a sound biological understanding have been evolving. The current experimental systems have many of the characteristics of biological computers (brains in other words) and are beginning to be built to perform a variety of tasks that are difficult or impossible to do with conventional computers. As evident, the ultimate achievement in this field would be to mimic or exceed human cognitive capabilities including reasoning, recognition, creativity, emotions, understanding, learning and so on. This book comprising of 17 chapters offers a step-by-step introduction (in a chronological order) to the various modern computational intelligence tools used in practical problem solving. Staring with different search techniques including informed and uninformed search, heuristic search, minmax, alpha-beta pruning methods, evolutionary algorithms and swarm intelligent techniques; the authors illustrate the design of knowledge-based systems and advanced expert systems, which incorporate uncertainty and fuzziness. Machine learning algorithms including decision trees and artificial neural networks are presented and finally the fundamentals of hybrid intelligent systems are also depicted. Academics, scientists as well as engineers engaged in research, development and application of computational intelligence techniques, machine learning and data mining would find the comprehensive coverage of this book invaluable.

Naturally Intelligent Systems offers a comprehensive introduction to neural networks.

Recent developments in soft-computation techniques have paved the way for handling huge volumes of data, thereby bringing about significant changes and technological advancements. This book presents the proceedings of the 3rd International Conference on Emerging Current Trends in Computing & Expert Technology (COMET 2020), held at Panimalar Engineering College, Chennai, India on 6 and 7 March 2020. The aim of the book is to disseminate cutting-edge developments taking place in the technological fields of intelligent systems and computer technology, thereby assisting researchers and practitioners from both institutions and industry to upgrade their knowledge of the latest developments and emerging areas of study. It focuses on technological innovations and trendsetting initiatives to improve business values, optimize business processes and enable inclusive growth for corporates, industries and education alike. The book is divided into two sections; ‘Next Generation Soft Computing’ is a platform for scientists, researchers, practitioners and academics to present and discuss their most recent innovations, trends and concerns, as well as the practical challenges encountered in the field. The second section, ‘Evolutionary Networking and Communications’ focuses on various aspects of 5G communications systems and networking, including cloud and virtualization solutions, management technologies, and vertical application areas. It brings together the latest technologies from all over the world, and also provides an excellent international forum for the sharing of knowledge and results from theory, methodology and applications in networking and communications. The book will be of interest to all those working in the fields of intelligent systems and computer technology.

Produce a fully functioning Intelligent System that leverages machine learning and data from user interactions to improve over time and achieve success. This book teaches you how to build an Intelligent System from end to end and leverage machine learning in practice. You will understand how to apply your existing skills in software engineering, data science, machine learning, management, and program management to produce working systems. Building Intelligent Systems is based on more than a decade of experience building Internet-scale Intelligent Systems that have hundreds of millions of user interactions per day in some of the largest and most important software systems in the world. What You’ll Learn Understand the concept of an Intelligent System: What it is good for, when you need one, and how to set it up for success Design an intelligent user experience: Produce data to help make the Intelligent System better over time Implement an Intelligent System: Execute, manage, and measure Intelligent Systems in practice Create intelligence: Use different approaches, including machine learning Orchestrate an Intelligent System: Bring the parts together throughout its life cycle and achieve the impact you want Who This Book Is For Software engineers, machine learning practitioners, and technical managers who want to build effective intelligent systems

The third edition of this bestseller examines the principles of artificial intelligence and their application to engineering and science, as well as techniques for developing intelligent systems to solve practical problems. Covering the full spectrum of intelligent systems techniques, it incorporates knowledge-based systems, computational intelligence, and their hybrids. Using clear and concise language, Intelligent Systems for Engineers and Scientists, Third Edition features updates and improvements throughout all chapters. It includes expanded and separated chapters on genetic algorithms and single-candidate optimization techniques, while the chapter on neural networks now covers spiking networks and a range of recurrent networks. The book also provides extended coverage of fuzzy logic, including type-2 and fuzzy control systems. Example programs using rules and uncertainty are presented in an industry-standard format, so that you can run them yourself. The first part of the book describes key techniques of artificial intelligence—including rule-based systems, Bayesian updating, certainty theory, fuzzy logic (types 1 and 2), frames, objects, agents, symbolic learning, case-based reasoning, genetic algorithms, optimization algorithms, neural networks, hybrids, and the Lisp and Prolog languages. The second part describes a wide range of practical applications in interpretation and diagnosis, design and selection, planning, and control. The author provides sufficient detail to help you develop your own intelligent systems for real applications. Whether you are building intelligent systems or you simply want to know more about them, this book provides you with detailed and up-to-date guidance. Check out the significantly expanded set of free web-based resources that support the book at: http://www.adrianhopgood.com/aitoolkit/

The 21st century has witnessed massive changes around the world in intelligence systems in order to become smarter, energy efficient, reliable, and cheaper. This volume explores the application of intelligent techniques in various fields of engineering and technology. It addresses diverse topics in such areas as machine learning-based intelligent systems for healthcare, applications of artificial intelligence and the Internet of Things, intelligent data analytics techniques, intelligent network systems and applications, and inequalities and process control systems. The authors explore the full breadth of the field, which encompasses data analysis, image processing, speech processing and recognition, medical science and healthcare monitoring, smart irrigation systems, insurance and banking, robotics and process control, and more.

Intelligent system is an advanced machine that can perceive, learn, and solve the problems with a great accuracy. Technologies with intelligent system are currently available in the market and used in real-world applications, i.e., self-driving cars, Siri, Alexa, Facebook, and so on. To exceed human cognitive capabilities, the important keys rely on the development of sensors and algorithms. Therefore, the insight into artificial intelligence (AI) methods becomes a fundamental building block for design and construction of intelligent system with particular applications. This book aims to describe the AI systems ranging from the basic knowledge, i.e., algorithm and mathematical models of AI techniques, fundamentals of machine learning, genetic algorithm, and fuzzy logic, to the current state-of-the-art applications, such as smart road and biomedical applications.

The deployment of intelligent systems to tackle complex processes is now commonplace in many fields from medicine and agriculture to industry and tourism. This book presents scientific contributions from the 1st International Conference on Applications of Intelligent Systems (APPIS 2018) held at the Museo Elder in Las Palmas de Gran Canaria, Spain, from 10 to 12 January 2018. The aim of APPIS 2018 was to bring together scientists working on the development of intelligent computer systems and methods for machine learning, artificial intelligence, pattern recognition, and related techniques with an emphasis on their application to various problems. The 34 peer-reviewed papers included here cover an extraordinarily wide variety of topics – everything from semi-supervised learning to matching electro-chemical sensor information with human odor perception – but what they all have in common is the design and application of intelligent systems and their role in tackling diverse and complex challenges. The book will be of particular interest to all those involved in the development and application of intelligent systems.

Keeping the maths to a minimum, Negnevitsky explains the principles of AI, demonstrates how systems are built, what they are useful for and how to choose the right tool for the job.

This book explores the latest research trends in intelligent systems and smart applications. It presents high-quality empirical and review studies focusing on various topics, including information systems and software engineering, knowledge management, technology in education, emerging technologies, and social networks. It provides insights into the theoretical and practical aspects of intelligent systems and smart applications.