This book gathers revised and extended versions of the best papers presented at the 8th International Joint Conference on Computational Intelligence (IJCCI 2016), which was held in Porto, Portugal from 9 to 11 November 2016. The papers address three main fields of Computational Intelligence, namely: Evolutionary Computation, Fuzzy Computation, and Neural Computation. In addition to highlighting recent advances in these areas, the book offers veteran researchers new and innovative solutions, while also providing a source of information and inspiration for newcomers to the field.

One of the goals of artificial intelligence (AI) is creating autonomous agents that must make decisions based on uncertain and incomplete information. The goal is to design rational agents that must take the best action given the information available and their goals. Decision Theory Models for Applications in Artificial Intelligence: Concepts and Solutions provides an introduction to different types of decision theory techniques, including MDPs, POMDPs, Influence Diagrams, and Reinforcement Learning, and illustrates their application in artificial intelligence. This book provides insights into the advantages and challenges of using decision theory models for developing intelligent systems.

In real management situations, uncertainty is inherently present in decision making. As such, it is increasingly imperative to research and develop new theories and methods of fuzzy sets. Theoretical and Practical Advancements for Fuzzy System Integration is a pivotal reference source for the latest scholarly research on the importance of expressing and measuring fuzziness in order to develop effective and practical decision making models and methods. Featuring coverage on an expansive range of perspectives and topics, such as fuzzy logic control, intuitionistic fuzzy set theory, and defuzzification, this book is ideally designed for academics, professionals, and researchers seeking current research on theoretical frameworks and real-world applications in the area of fuzzy sets and systems.

Advanced research in the field of mechatronics and robotics represents a unifying interdisciplinary and intelligent engineering science paradigm. It is a holistic, concurrent, and interdisciplinary engineering science that identifies novel possibilities of synergizing and fusing different disciplines. The Handbook of Research on Advanced Mechatronic Systems and Intelligent Robotics is a collection of innovative research on the methods and applications of knowledge in both theoretical and practical skills of intelligent robotics and mechatronics. While highlighting topics including green technology, machine learning, and virtual manufacturing, this book is ideally designed for researchers, students, engineers, and computer practitioners seeking current research on developing innovative ideas for intelligent robotics and autonomous and smart interdisciplinary mechatronic products.

This book highlights new trends and challenges in research on agents and the new digital and knowledge economy. It includes papers on business- process management, agent-based modeling and simulation, and anthropic-oriented computing, which were originally presented at the 13th International KES Conference on Agents and Multi-Agent Systems - Technologies and Applications (KES-AMSTA 2019) held June 17-19, 2019 at St George's Bay, St. Julians, Malta. Today's economy is driven by technologies and knowledge. Digital technologies can free, shift and multiply choices, and often intrude on the territory of other industries by providing new ways of conducting business operations and creating value for customers and companies. As such, the book covers topics such as software agents, multi-agent systems, agent modeling, mobile and cloud computing, big data analysis, business intelligence, artificial intelligence, social systems, computer embedded systems and nature inspired manufacturing, all of which contribute to the modern digital economy. The research presented is of value to researchers and industrial practitioners working in the fields of artificial intelligence, collective computational intelligence, innovative business models, the new digital and knowledge economy and, in particular, agent and multi-agent systems, technologies, tools and applications.

This book contains 74 papers presented at ICTCS 2017: Third International Conference on Information and Communication Technology for Competitive Strategies. The conference was held during 16-17 December 2017, Udaipur, India and organized by Association of Computing Machinery, Udaipur Professional Chapter in association with The Institution of Engineers (India), Udaipur Local Center and Global Knowledge Research Foundation. This book contains papers mainly focused on ICT for Computation, Algorithms and Data Analytics and IT Security etc.

The book presents innovative scientific research works by academics, research scholars and students, presented at the 2017 International Conference on Energy, Materials and Information Technology at Amity University Jharkhand, India. It includes contributions on system solutions based on soft computing techniques, and covers innovative soft computing techniques and tools with advanced applications. A major focus of the book is on presenting interdisciplinary problems and how they can be solved using information technology, together with innovative connections to other disciplines. It also includes papers on cloud computing and WSN-related real-time research.

This book introduces readers to the use of R codes for optimization problems. First, it provides the necessary background to understand data envelopment analysis (DEA), with a special emphasis on fuzzy DEA. It then describes DEA models, including fuzzy DEA models, and shows how to use them to solve optimization problems with R. Further, it discusses the main advantages of R in optimization problems, and provides R codes based on real-world data sets throughout. Offering a comprehensive review of DEA and fuzzy DEA models and the corresponding R codes, this practice-oriented reference guide is intended for masters and Ph.D. students in various disciplines, as well as practitioners and researchers.

Mapping and localization are two essential tasks in autonomous mobile robotics. Due to the unavoidable noise that sensors present, mapping algorithms usually rely on loop closure detection techniques, which entail the correct identification of previously seen places to reduce the uncertainty of the resulting maps. This book deals with the problem of generating topological maps of the environment using efficient appearance-based loop closure detection techniques. Since the quality of a visual loop closure detection algorithm is related to the image description method and its ability to index previously seen images, several methods for loop closure detection adopting different approaches are developed and assessed. Then, these methods are used in three novel topological mapping algorithms. The results obtained indicate that the solutions proposed attain a better performance than several state-of-the-art approaches. To conclude, given that loop closure detection is also a key component in other research areas, a multi-threaded image mosaicing algorithm is proposed. This approach makes use of one of the loop closure detection techniques previously introduced in order to find overlapping pairs between images and finally obtain seamless mosaics of different environments in a reasonable amount of time.

This book explores recent perspectives on type-2 fuzzy sets. Written as a tribute to Professor Jerry Mendel for his pioneering works on type-2 fuzzy sets and systems, it covers a wide range of topics, including applications to the Go game, machine learning and pattern recognition, as well as type-2 fuzzy control and intelligent systems. The book is intended as a reference guide for the type-2 fuzzy logic community, yet it aims also at other communities dealing with similar methods and applications.

This book highlights papers presented at the Second International Conference on Smart Vehicular Technology, Transportation, Communication and Applications (VTCA 2018), which was held at Mount Emei, Sichuan Province, China from 25 to 28 October 2018. The conference was co-sponsored by Springer, Southwest Jiaotong University, Fujian University of Technology, Chang'an University, Shandong University of Science and Technology, Fujian Provincial Key Lab of Big Data Mining and Applications, and the National Demonstration Center for Experimental Electronic Information and Electrical Technology Education (Fujian University of Technology). The conference was intended as an international forum for researchers and professionals engaged in all areas of smart vehicular technology, vehicular transportation, vehicular communication, and applications.

Cutting-edge research indicates that evolutionary programming is set to emerge as the dominant optimisation technique in the fast-changing power industry. Combining theory and practice, Intelligent System Applications in Power Engineering capitalises on the potential of neural networks and evolutionary computation to resolve real-world power engineering problems such as load forecasting, power system operation and planning optimisation. Unlike existing optimisation methods, these novel computational intelligence techniques provide power utilities with innovative solutions for improved performance. Features include:

• Introduction to evolutionary programming and neural networks serving as a foundation for later discussion of the benefits of hybrid systems
• Practical application of evolutionary programming to reactive power planning and dispatch for speedy, cost-effective increases in transmission capacity plus generator parameter estimation
• Examination of economic dispatch, power flow control in FACTS and co-generation scheduling and fault diagnosis for HVDC systems and transformers
• Consideration of power frequency and harmonic evaluation to maximise supply quality
• Employment of distance protection, faulty section estimation and calculation of fault clearing time for transient stability assessment

This book introduces readers to the background, general framework, main operators, and other basic characteristics of biogeography-based optimization (BBO), which is an emerging branch of bio-inspired computation. In particular, the book presents the authors' recent work on improved variants of BBO, hybridization of BBO with other algorithms, and the application of BBO to a variety of domains including transportation, image processing, and neural network learning. The content will help to advance research into and application of not only BBO but also the whole field of bio-inspired computation. The algorithms and applications are organized in a step-by-step manner and clearly described with the help of pseudo-codes and flowcharts. The readers will learn not only the basic concepts of BBO but also how to apply and adapt the algorithms to the engineering optimization problems they actually encounter.

These proceedings present selected research papers from CISC'18, held in Wenzhou, China. The topics include Multi-Agent Systems, Networked Control Systems, Intelligent Robots, Complex System Theory and Swarm Behavior, Event-Triggered Control and Data-Driven Control, Robust and Adaptive Control, Big Data and Brain Science, Process Control, Nonlinear and Variable Structure Control, Intelligent Sensor and Detection Technology, Deep learning and Learning Control Guidance, Navigation and Control of Flight Vehicles, and so on. Engineers and researchers from academia, industry, and government can get an insight view of the solutions combining ideas from multiple disciplines in the field of intelligent systems.

This volume focuses on smart medical and healthcare systems (modern intelligent systems for medicine and healthcare) and includes 31 papers presenting recent trends and innovations in medicine and healthcare, including biomedical engineering research and technologies; machine learning and labeling for biomedical visual data analysis and understanding; advanced ICT for medicine and healthcare; and healthcare support systems. Innovation in medicine and healthcare is an interdisciplinary research area, which combines advanced technologies and problem-solving skills with medical and biological science, and smart medical and healthcare systems can provide efficient and accurate solution to problems faced by healthcare and medical practitioners today by using advanced information communication techniques, computational intelligence, mathematics, robotics and other advanced technologies. Discussing the techniques developed in this area, which will have a significant effect on future medicine and healthcare, the book is a valuable resource for researchers, students, engineers, and professionals working in the fields of medical systems, medical technology, and intelligent systems.

Due to increasing potential in real-world applications such as visual communications, computer assisted biomedical imaging, and video surveillance, image and video interpretations have become an area of growing interest. Intelligent Image and Video Interpretation: Algorithms and Applications covers all aspects of image and video analysis from low-level early visions to high-level recognition. This publication highlights how these techniques have become applicable and will prove to be a valuable tool for researchers, professionals, and graduate students working or studying the fields of imaging and video processing.

Intelligent agents are employed as the central characters in this introductory text. Beginning with elementary reactive agents, Nilsson gradually increases their cognitive horsepower to illustrate the most important and lasting ideas in AI. Neural networks, genetic programming, computer vision, heuristic search, knowledge representation and reasoning, Bayes networks, planning, and language understanding are each revealed through the growing capabilities of these agents. A distinguishing feature of this text is in its evolutionary approach to the study of AI. This book provides a refreshing and motivating synthesis of the field by one of AI's master expositors and leading researches.

This book offers a detailed description of the histogram probabilistic multi-hypothesis tracker (H-PMHT), providing an accessible and intuitive introduction to the mathematical mechanics of H-PMHT as well as a definitive reference source for the existing literature on the method. Beginning with basic concepts, the authors then move on to address extensions of the method to a broad class of tracking problems. The latter chapters present applications using recorded data from experimental radar, sonar and video sensor systems. The book is supplemented with software that both furthers readers' understanding and acts as a toolkit for those who wish to apply the methods to their own problems.

Agenda Relevance is the first volume in the authors' omnibus investigation of
the logic of practical reasoning, under the collective title, A Practical Logic
of Cognitive Systems. In this highly original approach, practical reasoning is
identified as reasoning performed with comparatively few cognitive assets,
including resources such as information, time and computational capacity. Unlike
what is proposed in optimization models of human cognition, a practical reasoner
lacks perfect information, boundless time and unconstrained access to
computational complexity. The practical reasoner is therefore obliged to be a
cognitive economizer and to achieve his cognitive ends with considerable
efficiency. Accordingly, the practical reasoner avails himself of various
scarce-resource compensation strategies. He also possesses neurocognitive
traits that abet him in his reasoning tasks. Prominent among these is the
practical agent's striking (though not perfect) adeptness at evading irrelevant
information and staying on task. On the approach taken here, irrelevancies are
impediments to the attainment of cognitive ends. Thus, in its most basic sense,
relevant information is cognitively helpful information. Information can then be
said to be relevant for a practical reasoner to the extent that it advances or
closes some cognitive agenda of his. The book explores this idea with a
conceptual detail and nuance not seen the standard semantic, probabilistic and
pragmatic approaches to relevance; but wherever possible, the authors seek to
integrate alternative conceptions rather than reject them outright. A further
attraction of the agenda-relevance approach is the extent to which its principal
conceptual findings lend themselves to technically sophisticated re-expression
in formal models that marshal the resources of time and action logics and
label led deductive systems.

Agenda Relevance is necessary reading for researchers in logic, belief
dynamics, computer science, AI, psychology and neuroscience, linguistics,
argumentation theory, and legal reasoning and forensic science, and will repay
study by graduate students and senior undergraduates in these same fields.

Key features:

relevance
action and agendas
practical reasoning
belief dynamics
non-classical logics
labelled deductive systems

"

In the fast pace of the modern world it is important, more than ever, for factories to know how and why their machines are failing and what can be done to prevent it. As such, it is imperative that new research is conducted to make sure that factories can operate as efficiently as possible. Fuzzy Logic Dynamics and Machine Prediction for Failure Analysis is an essential reference source for the newest research on the risk assessment matrix, ladder logic, and computerized maintenance management systems (CMMS). Featuring widespread coverage across a variety of related viewpoints and topics, such as the Ishikawa diagram, machinery failure analysis and troubleshooting, model reference adaptive control systems, and proportional-integral-derivative (PID) controllers, this book is ideally designed for professionals, upper-level students, and academics seeking current research on the implementation of fuzzy logic in machine prediction failure.

This book addresses new challenges and emerging ideas in Distributed Information Filtering and Retrieval. It gathers extended papers presented at DART 2013 (the 7th International Workshop on Information Filtering and Retrieval), held on December 6, 2013 in Turin, Italy, and co-hosted with the XIII International Conference of the Italian Association for Artificial Intelligence. The main focus of DART was to discuss and compare suitable novel solutions based on intelligent techniques and applied to real-world contexts. The papers presented here offer a comprehensive review of related work and state-of-the-art techniques. The authors - a mix of respected practitioners and researchers - share their findings on a range of topics, including data leak protection on text comparison, natural language processing, ambient intelligence, information retrieval and web portals, and knowledge management. All contributions were carefully reviewed by experts in the respective area, who also provided useful suggestions to improve the book's overall quality.

Computer vision and object recognition are two technological methods that are frequently used in various professional disciplines. In order to maintain high levels of quality and accuracy of services in these sectors, continuous enhancements and improvements are needed. The implementation of artificial intelligence and machine learning has assisted in the development of digital imaging, yet proper research on the applications of these advancing technologies is lacking. Applications of Advanced Machine Intelligence in Computer Vision and Object Recognition: Emerging Research and Opportunities explores the theoretical and practical aspects of modern advancements in digital image analysis and object detection as well as its applications within healthcare, security, and engineering fields. Featuring coverage on a broad range of topics such as disease detection, adaptive learning, and automated image segmentation, this book is ideally designed for engineers, physicians, researchers, academicians, practitioners, scientists, industry professionals, scholars, and students seeking research on the current developments in object recognition using artificial intelligence.

Wagman gives a broad, structured, and detailed account of advancing intellectual developments in both psychological and computational theories of the nature of problem- solving. Known for originating the PLATO computer-based Dilemma Counseling System, psychologist Wagman is the author of 17 books, including "Scientific Discovery Processes in Humans and Computers "(Praeger, 2000).

In this book, Professor Emeritus Morton Wagman gives a broad, structured, and detailed account of advancing intellectual developments in both psychological and computational theories of the nature of problem solving. Known for originating the PLATO computer-based Dilemma Counseling System, psychologist Wagman is the author of 17 books, including "Scientific Discovery Processes in Humans and Computers, "(Praeger, 2000)

Of special interest to readers will be Wagman's conclusion that artificial intelligence problem-solving systems are deepening and broadening theories of human problem solving from scientific to everyday approaches. Scholars and professionals in psychology, artificial intelligence, and cognitive science will consider this a volume a valuable addition to their collections.