"Efficient Computation of Argumentation Semantics" addresses argumentation semantics and systems, introducing readers to cutting-edge decomposition methods that drive increasingly efficient logic computation in AI and intelligent systems. Such complex and distributed systems are increasingly used in the automation and transportation systems field, and particularly autonomous systems, as well as more generic intelligent computation research.

The Series in Intelligent Systems publishes titles that cover state-of-the-art knowledge and the latest advances in research and development in intelligent systems. Its scope includes theoretical studies, design methods, and real-world implementations and applications. The series publishes titles in three core sub-topic areas: intelligent automation, intelligent transportation systems, and intelligent computing.
The first book to cover new methods for computing static, dynamic, and partial argumentation systemsMethods are applicable to development of systems and research areas in both AI and broader intelligent systemsProvides the AI and IS community with insight into the critical field of efficient computation, with a focus on intelligent automation, intelligent transportation systems, and intelligent computing

The theme of this book is the self-generation of information by the self-modification of systems. The author explains why biological and cognitive processes exhibit identity changes in the mathematical and logical sense. This concept is the basis of a new organizational principle which utilizes shifts of the internal semantic relations in systems. There are mathematical discussions of various classes of systems (Turing machines, input-output systems, synergetic systems, non-linear dynamics etc), which are contrasted with the author's new principle. The most important implications of this include a new conception on the nature of information and which also provides a new and coherent conceptual view of a wide class of natural systems. This book merits the attention of all philosophers and scientists concerned with the way we create reality in our mathematical representations of the world and the connection those representations have with the way things really are.

This book contains selected papers from the 9th International Conference on Information Science and Applications (ICISA 2018) and provides a snapshot of the latest issues encountered in technical convergence and convergences of security technology. It explores how information science is core to most current research, industrial and commercial activities and consists of contributions covering topics including Ubiquitous Computing, Networks and Information Systems, Multimedia and Visualization, Middleware and Operating Systems, Security and Privacy, Data Mining and Artificial Intelligence, Software Engineering, and Web Technology. The proceedings introduce the most recent information technology and ideas, applications and problems related to technology convergence, illustrated through case studies, and reviews converging existing security techniques. Through this volume, readers will gain an understanding of the current state-of-the-art information strategies and technologies of convergence security. The intended readership includes researchers in academia, industry and other research institutes focusing on information science and technology.

This book explores and evaluates accounts and models of autistic reasoning and cognition from a computational standpoint. The author investigates the limitations and peculiarities of autistic reasoning and sets out a remediation strategy to be used by a wide range of psychologists and rehabilitation personnel and will also be appreciated by computer scientists who are interested in the practical implementation of reasoning. The author subjects the Theory of Mind (ToM) model to a formal analysis to investigate the limitations of autistic reasoning and proposes a formal model regarding mental attitudes and proposes a method to help those with autism navigate everyday living. Based on the concept of playing with computer based mental simulators, the NL_MAMS, is examined to see whether it is capable of modeling mental and emotional states of the real world to aid the emotional development of autistic children. Multiple autistic theories and strategies are also examined for possible computational cross-overs, providing researchers with a wide range of examples, tools and detailed case studies to work from. Computational Autism will be an essential read to behavioral specialists, researcher's, developers and designers who are interested in understanding and tackling the increasing prevalence of autism within modern society today.

This book features selected papers presented at The International Science and Technology Conference "FarEastCon", which took place on October 2-4, 2018 in Vladivostok, Russian Federation. The conference represents an informational platform for accumulating expert opinion on projects and initiatives aimed at the implementation of farsighted scientific research and development; it also allows scientific and practical achievements to be shared with a wide circle of researchers. Sections of the conference are of interest for the broad range of experts involved in developing innovative solutions and organizing events that increase the efficiency of economic and innovative activities.

From finance to artificial intelligence, genetic algorithms are a powerful tool with a wide array of applications. But you don't need an exotic new language or framework to get started; you can learn about genetic algorithms in a language you're already familiar with. Join us for an in-depth look at the algorithms, techniques, and methods that go into writing a genetic algorithm. From introductory problems to real-world applications, you'll learn the underlying principles of problem solving using genetic algorithms. Evolutionary algorithms are a unique and often overlooked subset of machine learning and artificial intelligence. Because of this, most of the available resources are outdated or too academic in nature, and none of them are made with Elixir programmers in mind. Start from the ground up with genetic algorithms in a language you are familiar with. Discover the power of genetic algorithms through simple solutions to challenging problems. Use Elixir features to write genetic algorithms that are concise and idiomatic. Learn the complete life cycle of solving a problem using genetic algorithms. Understand the different techniques and fine-tuning required to solve a wide array of problems. Plan, test, analyze, and visualize your genetic algorithms with real-world applications. Open your eyes to a unique and powerful field - without having to learn a new language or framework. What You Need: You'll need a macOS, Windows, or Linux distribution with an up-to-date Elixir installation.

What are the limitations of computer models and why do we still not have working models of people that are recognizably human? This is the principle puzzle explored in this book where ideas behind systems that behave intelligently are described and different philosophical issues are touched upon. The key to human behavior is taken to be intelligence and the ability to reason about the world. A strong scientific approach is taken, but first it was required to understand what a scientific approach could mean in the context of both natural and artificial systems. A theory of intelligence is proposed that can be tested and developed in the light of experimental results. The book illustrates that intelligence is much more than just behavior confined to a unique person or a single computer program within a fixed time frame. Some answers are unraveled and some puzzles emerge from these investigations and experiments. Natural and Artificial Reasoning provides a few steps of an exciting journey that began many centuries ago with the word 'why?'

This book primarily addresses Intelligent Information Systems (IIS) and the integration of artificial intelligence, intelligent systems and technologies, database technologies and information systems methodologies to create the next generation of information systems. It includes original and state-of-the-art research on theoretical and practical advances in IIS, system architectures, tools and techniques, as well as "success stories" in intelligent information systems. Intended as an interdisciplinary forum in which scientists and professionals could share their research results and report on new developments and advances in intelligent information systems, technologies and related areas - as well as their applications - , it offers a valuable resource for researchers and practitioners alike.

This book presents a novel framework, known as Active Robust Optimization, which provides the tools for evaluating, comparing and optimizing changeable products. Since any product that can change its configuration during normal operation may be considered a "changeable product," the framework is widely applicable. Further, the methodology enables designers to use adaptability to deal with uncertainties and so avoid over-conservative designs. Offering a comprehensive overview of the framework, including its unique features, such as its ability to optimally respond to uncertain situations, the book also defines a new class of optimization problem and examines the effects of changes in various parameters on their solution. Lastly, it discusses innovative approaches for solving the problem and demonstrates these with two examples from different fields in engineering design: optimization of an optical table and optimization of a gearbox.

This volume presents a collection of original research works by leading specialists focusing on novel and promising approaches in which the multi-agent system paradigm is used to support, enhance or replace traditional approaches to solving difficult optimization problems. The editors have invited several well-known specialists to present their solutions, tools, and models falling under the common denominator of the agent-based optimization. The book consists of eight chapters covering examples of application of the multi-agent paradigm and respective customized tools to solve difficult optimization problems arising in different areas such as machine learning, scheduling, transportation and, more generally, distributed and cooperative problem solving.

This book provides a self-study program on how mathematics, computer science and science can be usefully and seamlessly intertwined. Learning to use ideas from mathematics and computation is essential for understanding approaches to cognitive and biological science. As such the book covers calculus on one variable and two variables and works through a number of interesting first-order ODE models. It clearly uses MatLab in computational exercises where the models cannot be solved by hand, and also helps readers to understand that approximations cause errors - a fact that must always be kept in mind.

This book introduces and illustrates modeling, sensing, and control methods for analyzing, designing, and developing spherical motors. It systematically presents models for establishing the relationships among the magnetic fields, position/orientation and force/torque, while also providing time-efficient solutions to assist researchers and engineers in studying and developing these motors. In order to take full advantage of spherical motors' compact structure in practical applications, sensing and control methods that utilize their magnetic fields and eliminate the need to install external sensors for feedback are proposed. Further, the book investigates for the first time spherical motors' force/torque manipulation capability, and proposes algorithms enabling the ball-joint-like end-effector for haptic use based on these motors' hybrid position/force actuation modes. While systematically presenting approaches to their design, sensing and control, the book also provides many examples illustrating the implementation issues readers may encounter.

Genetic Regulatory Networks (GRNs) in biological organisms are primary engines for cells to enact their engagements with environments, via incessant, continually active coupling. In differentiated multicellular organisms, tremendous complexity has arisen in the course of evolution of life on earth. Engineering and science have so far achieved no working system that can compare with this complexity, depth and scope of organization. Abstracting the dynamics of genetic regulatory control to a computational framework in which artificial GRNs in artificial simulated cells differentiate while connected in a changing topology, it is possible to apply Darwinian evolution in silico to study the capacity of such developmental/differentiated GRNs to evolve. In this volume an evolutionary GRN paradigm is investigated for its evolvability and robustness in models of biological clocks, in simple differentiated multicellularity, and in evolving artificial developing 'organisms' which grow and express an ontogeny starting from a single cell interacting with its environment, eventually including a changing local neighbourhood of other cells. These methods may help us understand the genesis, organization, adaptive plasticity, and evolvability of differentiated biological systems, and may also provide a paradigm for transferring these principles of biology's success to computational and engineering challenges at a scale not previously conceivable.

Demystify the world of artificial intelligence with this groundbreaking guide featuring over 100 innovative ways to incorporate AI into your daily life.

Every day, it seems like there’s a new AI tool on the market and a new, complicated way to use it. But what if you could use AI to make your life easier without the complications?

In AI for Life, AI expert and creator of @SmartWorkAI offers over 100 ideas and ready-to-use prompts to get AI beginners started using the technology to actually improve their lives. Beginning with a primer on the basics—including an overview of the popular and free AI tools—you will learn expert-tested tips and tricks to get the most out of your AI use, such as layering prompts to dive deeper into an initial response or asking for the output in different formats.

Packed with practical how-to information, AI for Life is the must-have guide for using generative AI to make life easier, more productive, more organized, and more fun!

This book contains the full papers presented at the MICCAI 2013 workshop Bio-Imaging and Visualization for Patient-Customized Simulations (MWBIVPCS 2013). MWBIVPCS 2013 brought together researchers representing several fields, such as Biomechanics, Engineering, Medicine, Mathematics, Physics and Statistic.

The contributions included in this book present and discuss new trends in those fields, using several methods and techniques, including the finite element method, similarity metrics, optimization processes, graphs, hidden Markov models, sensor calibration, fuzzy logic, data mining, cellular automation, active shape models, template matching and level sets. These serve as tools to address more efficiently different and timely applications involving signal and image acquisition, image processing and analysis, image segmentation, image registration and fusion, computer simulation, image based modelling, simulation and surgical planning, image guided robot assisted surgical and image based diagnosis.

This book will appeal to researchers, PhD students and graduate students with multidisciplinary interests related to the areas of medical imaging, image processing and analysis, computer vision, image segmentation, image registration and fusion, scientific data visualization and image based modeling and simulation.

Biological and other natural processes have always been a source of inspiration for computer science and information technology. Many emerging problem solving techniques integrate advanced evolution and cooperation strategies, encompassing a range of spatio-temporal scales for visionary conceptualization of evolutionary computation. This book is a collection of research works presented in the VI International Workshop on Nature Inspired Cooperative Strategies for Optimization (NICSO) held in Canterbury, UK. Previous editions of NICSO were held in Granada, Spain (2006 & 2010), Acireale, Italy (2007), Tenerife, Spain (2008), and Cluj-Napoca, Romania (2011). NICSO 2013 and this book provides a place where state-of-the-art research, latest ideas and emerging areas of nature inspired cooperative strategies for problem solving are vigorously discussed and exchanged among the scientific community. The breadth and variety of articles in this book report on nature inspired methods and applications such as Swarm Intelligence, Hyper-heuristics, Evolutionary Algorithms, Cellular Automata, Artificial Bee Colony, Dynamic Optimization, Support Vector Machines, Multi-Agent Systems, Ant Clustering, Evolutionary Design Optimisation, Game Theory and other several Cooperation Models.

This book provides cutting-edge insights into autonomous vehicles and road terrain classification, and introduces a more rational and practical method for identifying road terrain. It presents the MRF algorithm, which combines the various sensors' classification results to improve the forward LRF for predicting upcoming road terrain types. The comparison between the predicting LRF and its corresponding MRF show that the MRF multiple-sensor fusion method is extremely robust and effective in terms of classifying road terrain. The book also demonstrates numerous applications of road terrain classification for various environments and types of autonomous vehicle, and includes abundant illustrations and models to make the comparison tables and figures more accessible.

Creating Knowledge Based Organizations brings together high quality concepts closely related to organizational learning, knowledge workers, intellectual capital, virtual teams and will include the methodologies, systems and approaches needed to create and manager knowledge-based organizations of the 21st Century.

This book introduces Local Binary Patterns (LBP), arguably one of the most powerful texture descriptors, and LBP variants. This volume provides the latest reviews of the literature and a presentation of some of the best LBP variants by researchers at the forefront of textual analysis research and research on LBP descriptors and variants. The value of LBP variants is illustrated with reported experiments using many databases representing a diversity of computer vision applications in medicine, biometrics, and other areas. There is also a chapter that provides an excellent theoretical foundation for texture analysis and LBP in particular. A special section focuses on LBP and LBP variants in the area of face recognition, including thermal face recognition. This book will be of value to anyone already in the field as well as to those interested in learning more about this powerful family of texture descriptors.

Much work on fuzzy control, covering research, development and applications, has been developed in Europe since the 90's. Nevertheless, the existing books in the field are compilations of articles without interconnection or logical structure or they express the personal point of view of the author. This book compiles the developments of researchers with demonstrated experience in the field of fuzzy control following a logic structure and a unified the style. The first chapters of the book are dedicated to the introduction of the main fuzzy logic techniques, where the following chapters focus on concrete applications. This book is supported by the EUSFLAT and CEA-IFAC societies, which include a large number of researchers in the field of fuzzy logic and control. The central topic of the book, Fuzzy Control, is one of the main research and development lines covered by these associations.

This book describes an effective framework for setting the right process parameters and new mold design to reduce the current plastic defects in injection molding. It presents a new approach for the optimization of injection molding process via (i) a new mold runner design which leads to 20 percent reduction in scrap rate, 2.5 percent reduction in manufacturing time, and easier ejection of injected part, (ii) a new mold gate design which leads to less plastic defects; and (iii) the introduction of a number of promising alternatives with high moldability indices. Besides presenting important developments of relevance academic research, the book also includes useful information for people working in the injection molding industry, especially in the green manufacturing field.

Every day decision making and decision making in complex human-centric systems are characterized by imperfect decision-relevant information. Main drawback of the existing decision theories is namely incapability to deal with imperfect information and modeling vague preferences. Actually, a paradigm of non-numerical probabilities in decision making has a long history and arose also in Keynes's analysis of uncertainty. There is a need for further generalization - a move to decision theories with perception-based imperfect information described in NL. The languages of new decision models for human-centric systems should be not languages based on binary logic but human-centric computational schemes able to operate on NL-described information. Development of new theories is now possible due to an increased computational power of information processing systems which allows for computations with imperfect information, particularly, imprecise and partially true information, which are much more complex than computations over numbers and probabilities.

The monograph exposes the foundations of a new decision theory with imperfect decision-relevant information on environment and a decision maker's behavior. This theory is based on the synthesis of the fuzzy sets theory with perception-based information and the probability theory.

The book is self containing and represents in a systematic way the decision theory with imperfect information into the educational systems. The book will be helpful for teachers and students of universities and colleges, for managers and specialists from various fields of business and economics, production and social sphere.

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These papers on Intelligent Data Analysis and Management (IDAM) examine issues related to the research and applications of Artificial Intelligence techniques in data analysis and management across a variety of disciplines. The papers derive from the 2013 IDAM conference in Kaohsiung ,Taiwan. It is an interdisciplinary research field involving academic researchers in information technologies, computer science, public policy, bioinformatics, medical informatics, and social and behavior studies, etc. The techniques studied include (but are not limited to): data visualization, data pre-processing, data engineering, database mining techniques, tools and applications, evolutionary algorithms, machine learning, neural nets, fuzzy logic, statistical pattern recognition, knowledge filtering, and post-processing, etc.

This special book is dedicated to the memory of Professor Zdzislaw Pawlak, the father of rough set theory, in order to commemorate both the 10th anniversary of his passing and 35 years of rough set theory. The book consists of 20 chapters distributed into four sections, which focus in turn on a historical review of Professor Zdzislaw Pawlak and rough set theory; a review of the theory of rough sets; the state of the art of rough set theory; and major developments in rough set based data mining approaches. Apart from Professor Pawlak's contributions to rough set theory, other areas he was interested in are also included. Moreover, recent theoretical studies and advances in applications are also presented. The book will offer a useful guide for researchers in Knowledge Engineering and Data Mining by suggesting new approaches to solving the problems they encounter.

This book provides a systematic and comprehensive description of Non-Axiomatic Logic, which is the result of the author's research for about three decades.Non-Axiomatic Logic is designed to provide a uniform logical foundation for Artificial Intelligence, as well as an abstract description of the "laws of thought" followed by the human mind. Different from "mathematical" logic, where the focus is the regularity required when demonstrating mathematical conclusions, Non-Axiomatic Logic is an attempt to return to the original aim of logic, that is, to formulate the regularity in actual human thinking. To achieve this goal, the logic is designed under the assumption that the system has insufficient knowledge and resources with respect to the problems to be solved, so that the "logical conclusions" are only valid with respect to the available knowledge and resources. Reasoning processes according to this logic covers cognitive functions like learning, planning, decision making, problem solving, etc.This book is written for researchers and students in Artificial Intelligence and Cognitive Science, and can be used as a textbook for courses at graduate level, or upper-level undergraduate, on Non-Axiomatic Logic.