"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

This edited book presents scientific results of 15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2014) held on June 30 - July 2, 2014 in Las Vegas Nevada, USA. The aim of this conference was to bring together scientists, engineers, computer users, and students to share their experiences and exchange new ideas, research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The conference organizers selected the 13 outstanding papers from those papers accepted for presentation at the conference.

Humanoid robotics have made remarkable progress since the dawn of robotics. So why don't we have humanoid robot assistants in day-to-day life yet? This book analyzes the keys to building a successful humanoid robot for field robotics, where collisions become an unavoidable part of the game. The

author argues that the design goal should be real anthropomorphism, as opposed to mere human-like appearance. He deduces three major characteristics to aim for when designing a humanoid robot, particularly robot hands:

_ Robustness against impacts

_ Fast dynamics

_ Human-like grasping and manipulation performance

Instead of blindly copying human anatomy, this book opts for a holistic design me-tho-do-lo-gy. It analyzes human hands and existing robot hands to elucidate the important functionalities that are the building blocks toward these necessary characteristics.They are the keys to designing an anthropomorphic robot hand, as illustrated in the high performance anthropomorphic Awiwi Hand presented in this book.

This is not only a handbook for robot hand designers. It gives a comprehensive survey and analysis of the state of the art in robot hands as well as the human anatomy. It is also aimed at researchers and roboticists interested in the underlying functionalities of hands, grasping and manipulation.

The methodology of functional abstraction is not limited to robot hands, it can also help realize a new generation of humanoid robots to accommodate a broader spectrum of the needs of human society."

This book presents advanced control techniques that use neural networks to deal with grid disturbances in the context renewable energy sources, and to enhance low-voltage ride-through capacity, which is a vital in terms of ensuring that the integration of distributed energy resources into the electrical power network. It presents modern control algorithms based on neural identification for different renewable energy sources, such as wind power, which uses doubly-fed induction generators, solar power, and battery banks for storage. It then discusses the use of the proposed controllers to track doubly-fed induction generator dynamics references: DC voltage, grid power factor, and stator active and reactive power, and the use of simulations to validate their performance. Further, it addresses methods of testing low-voltage ride-through capacity enhancement in the presence of grid disturbances, as well as the experimental validation of the controllers under both normal and abnormal grid conditions. The book then describes how the proposed control schemes are extended to control a grid-connected microgrid, and the use of an IEEE 9-bus system to evaluate their performance and response in the presence of grid disturbances. Lastly, it examines the real-time simulation of the entire system under normal and abnormal conditions using an Opal-RT simulator.

This book presents the state of the art in reinforcement learning applied to robotics both in terms of novel algorithms and applications. It discusses recent approaches that allow robots to learn motor.

skills and presents tasks that need to take into account the dynamic behavior of the robot and its environment, where a kinematic movement plan is not sufficient. The book illustrates a method that learns to generalize parameterized motor plans which is obtained by imitation or reinforcement learning, by adapting a small set of global parameters and appropriate kernel-based reinforcement learning algorithms. The presented applications explore highly dynamic tasks and exhibit a very efficient learning process. All proposed approaches have been extensively validated with benchmarks tasks, in simulation and on real robots. These tasks correspond to sports and games but the presented techniques are also applicable to more mundane household tasks. The book is based on the first author s doctoral thesis, which won the 2013 EURON Georges Giralt PhD Award."

This thesis provides a systematic and integral answer to an open problem concerning the universality of dynamic fuzzy controllers. It presents a number of novel ideas and approaches to various issues including universal function approximation, universal fuzzy models, universal fuzzy stabilization controllers, and universal fuzzy integral sliding mode controllers. The proposed control design criteria can be conveniently verified using the MATLAB toolbox. Moreover, the thesis provides a new, easy-to-use form of fuzzy variable structure control. Emphasis is given to the point that, in the context of deterministic/stochastic systems in general, the authors are in fact discussing non-affine nonlinear systems using a class of generalized T-S fuzzy models, which offer considerable potential in a wide range of applications.

Deep Learning Approaches for Security Threats in IoT Environments An expert discussion of the application of deep learning methods in the IoT security environment In Deep Learning Approaches for Security Threats in IoT Environments, a team of distinguished cybersecurity educators deliver an insightful and robust exploration of how to approach and measure the security of Internet-of-Things (IoT) systems and networks. In this book, readers will examine critical concepts in artificial intelligence (AI) and IoT, and apply effective strategies to help secure and protect IoT networks. The authors discuss supervised, semi-supervised, and unsupervised deep learning techniques, as well as reinforcement and federated learning methods for privacy preservation. This book applies deep learning approaches to IoT networks and solves the security problems that professionals frequently encounter when working in the field of IoT, as well as providing ways in which smart devices can solve cybersecurity issues. Readers will also get access to a companion website with PowerPoint presentations, links to supporting videos, and additional resources. They'll also find: A thorough introduction to artificial intelligence and the Internet of Things, including key concepts like deep learning, security, and privacy Comprehensive discussions of the architectures, protocols, and standards that form the foundation of deep learning for securing modern IoT systems and networks In-depth examinations of the architectural design of cloud, fog, and edge computing networks Fulsome presentations of the security requirements, threats, and countermeasures relevant to IoT networks Perfect for professionals working in the AI, cybersecurity, and IoT industries, Deep Learning Approaches for Security Threats in IoT Environments will also earn a place in the libraries of undergraduate and graduate students studying deep learning, cybersecurity, privacy preservation, and the security of IoT networks.

Information is becoming the raw material of modern society; it is the driving force of modern service industries. Our information spaces have been pervaded by technology and are characterized by their increasing size and complexity. Furthermore, access to information spaces and the ability to use them effectively and efficiently have become key economic success factors. Interdisciplinary Advances in Adaptive and Intelligent Assistant Systems: Concepts, Techniques, Applications, and Use encourages knowledge on effective and efficient approaches to accessing information spaces. It fosters an emerging key competence: accessing and processing large, highly complex corpora of information by applying collaborative, intelligent technical systems. It is the mission of this book to trigger interdisciplinary research and cooperation at the intersection between information sciences, information technologies and communication sciences. This publication also raises awareness of the field s importance in business and management communities, thus contributing to the dissemination of scientific ideas and insights.

This book at hand explores emerging scientific and technological areas in which Intelligent Computing Systems provide efficient solutions and, thus, may play a role in the years to come. It demonstrates how Intelligent Computing Systems make use of computational methodologies that mimic nature-inspired processes to address real world problems of high complexity for which exact mathematical solutions, based on physical and statistical modelling, are intractable. Common intelligent computational methodologies are presented including artificial neural networks, evolutionary computation, genetic algorithms, artificial immune systems, fuzzy logic, swarm intelligence, artificial life, virtual worlds and hybrid methodologies based on combinations of the previous. The book will be useful to researchers, practitioners and graduate students dealing with mathematically-intractable problems. It is intended for both the expert/researcher in the field of Intelligent Computing Systems, as well as for the general reader in the fields of Artificial and Computational Intelligence who wishes to learn more about the field of Intelligent Computing Systems and its applications. An extensive list of bibliographic references at the end of each chapter guides the reader to probe further into application area of interest to him/her.

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.

This book presents new findings in industrial cyber-physical system design and control for various domains, as well as their social and economic impacts on society. Industry 4.0 requires new approaches in the context of secure connections, control, and maintenance of cyber-physical systems as well as enhancing their interaction with humans. The book focuses on open issues of cyber-physical system control and its usage, discussing implemented breakthrough systems, models, programs, and methods that could be used in industrial processes for the control, condition assessment, diagnostics, prognostication, and proactive maintenance of cyber-physical systems. Further, it addresses the topic of ensuring the cybersecurity of industrial cyber-physical systems and proposes new, reliable solutions. The authors also examine the impact of university courses on the performance of industrial complexes, and the organization of education for the development of cyber-physical systems. The book is intended for practitioners, enterprise representatives, scientists, students, and Ph.D. and master's students conducting research in the area of cyber-physical system development and implementation in various domains.

This book constitutes the refereed post-conference proceedings of the 10th IFIP WG 5.14 International Conference on Computer and Computing Technologies in Agriculture, CCTA 2016, held in Dongying, China, in October 2016. The 55 revised papers presented were carefully reviewed and selected from 128 submissions. They cover a wide range of interesting theories and applications of information technology in agriculture, including intelligent sensing, cloud computing, key technologies of the Internet of Things, precision agriculture, animal husbandry information technology, including Internet + modern animal husbandry, livestock big data platform and cloud computing applications, intelligent breeding equipment, precision production models, water product networking and big data , including fishery IoT, intelligent aquaculture facilities, and big data applications.

The objective of this book is to contribute to the development of the intelligent information and database systems with the essentials of current knowledge, experience and know-how. The book contains a selection of 40 chapters based on original research presented as posters during the 8th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2016) held on 14-16 March 2016 in Da Nang, Vietnam. The papers to some extent reflect the achievements of scientific teams from 17 countries in five continents. The volume is divided into six parts: (a) Computational Intelligence in Data Mining and Machine Learning, (b) Ontologies, Social Networks and Recommendation Systems, (c) Web Services, Cloud Computing, Security and Intelligent Internet Systems, (d) Knowledge Management and Language Processing, (e) Image, Video, Motion Analysis and Recognition, and (f) Advanced Computing Applications and Technologies. The book is an excellent resource for researchers, those working in artificial intelligence, multimedia, networks and big data technologies, as well as for students interested in computer science and other related fields.

This volume is the first of the new series Advances in Dynamics and Delays. It offers the latest advances in the research of analyzing and controlling dynamical systems with delays, which arise in many real-world problems. The contributions in this series are a collection across various disciplines, encompassing engineering, physics, biology, and economics, and some are extensions of those presented at the IFAC (International Federation of Automatic Control) conferences since 2011. The series is categorized in five parts covering the main themes of the contributions: * Stability Analysis and Control Design * Networks and Graphs * Time Delay and Sampled-Data Systems * Computational and Software Tools * Applications This volume will become a good reference point for researchers and PhD students in the field of delay systems, and for those willing to learn more about the field, and it will also be a resource for control engineers, who will find innovative control methodologies for relevant applications, from both theory and numerical analysis perspectives.

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.

Organizational Efficiency through Intelligent Information Technologies explores various aspects of design and development of intelligent technologies by bringing together the latest in research in the fields of information systems, intelligent agents, collaborative works, and much more. This reference source also highlights insights on agent-based problem solving as well as economic issues and organizational impact.

This volume provides the audience with an updated, in-depth and highly coherent material on the conceptually appealing and practically sound information technology of Computational Intelligence applied to the analysis, synthesis and evaluation of social networks. The volume involves studies devoted to key issues of social networks including community structure detection in networks, online social networks, knowledge growth and evaluation, and diversity of collaboration mechanisms. The book engages a wealth of methods of Computational Intelligence along with well-known techniques of linear programming, Formal Concept Analysis, machine learning, and agent modeling. Human-centricity is of paramount relevance and this facet manifests in many ways including personalized semantics, trust metric, and personal knowledge management; just to highlight a few of these aspects. The contributors to this volume report on various essential applications including cyber attacks detection, building enterprise social networks, business intelligence and forming collaboration schemes.

Given the subject area, this book is aimed at a broad audience of researchers and practitioners. Owing to the nature of the material being covered and a way it is organized, the volume will appeal to the well-established communities including those active in various disciplines in which social networks, their analysis and optimization are of genuine relevance. Those involved in operations research, management, various branches of engineering, and economics will benefit from the exposure to the subject matter.

This book presents a comprehensive overview of security issues in Cyber Physical Systems (CPSs), by analyzing the issues and vulnerabilities in CPSs and examining state of the art security measures. Furthermore, this book proposes various defense strategies including intelligent attack and anomaly detection algorithms. Today's technology is continually evolving towards interconnectivity among devices. This interconnectivity phenomenon is often referred to as Internet of Things (IoT). IoT technology is used to enhance the performance of systems in many applications. This integration of physical and cyber components within a system is associated with many benefits; these systems are often referred to as Cyber Physical Systems (CPSs). The CPSs and IoT technologies are used in many industries critical to our daily lives. CPSs have the potential to reduce costs, enhance mobility and independence of patients, and reach the body using minimally invasive techniques. Although this interconnectivity of devices can pave the road for immense advancement in technology and automation, the integration of network components into any system increases its vulnerability to cyber threats. Using internet networks to connect devices together creates access points for adversaries. Considering the critical applications of some of these devices, adversaries have the potential of exploiting sensitive data and interrupting the functionality of critical infrastructure. Practitioners working in system security, cyber security & security and privacy will find this book valuable as a reference. Researchers and scientists concentrating on computer systems, large-scale complex systems, and artificial intelligence will also find this book useful as a reference.

This book presents the proceedings of the International Science and Technology Conference "FarEastCon 2019," which took place on October 1-4, 2019, in Vladivostok, Russian Federation. The conference provided a platform for gathering expert opinions on projects and initiatives aimed at the implementation of far-sighted scientific research and development, and allowed current theoretical and practical advances to be shared with the broader research community. Featuring selected papers from the conference, this book will be of interest to experts in various fields whose work involves developing innovative solutions and increasing the efficiency of economic activities.

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 describes the common ground between electricity markets (EMs) and software agents (or artificial intelligence generally). It presents an up-to-date introduction to EMs and intelligent agents, and offers a comprehensive description of the research advances and key achievements related to existing and emerging market designs to reliably and efficiently manage the potential challenges of variable generation (VG). Most EMs are unique in their complex relationships between economics and the physics of energy, but were created without the notion that large penetrations of variable generation (VG) would be part of the supply mix. An advanced multi-agent approach simulates the behavior of power markets over time, particularly markets with large-scale penetrations of renewable resources. It is intended as a reference book for researchers, academics and industry practitioners, but given the scope of the chapters and the highly accessible style, the book also provides a coherent foundation for several different graduate courses.

This volume contains nineteen research papers belonging to the areas of computational statistics, data mining, and their applications. Those papers, all written specifically for this volume, are their authors' contributions to honour and celebrate Professor Jacek Koronacki on the occcasion of his 70th birthday. The book's related and often interconnected topics, represent Jacek Koronacki's research interests and their evolution. They also clearly indicate how close the areas of computational statistics and data mining are.

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 emerged out of a project initiated and funded by the Defense Advanced Research Projects Agency (DARPA) that sought to build on efforts to transform agent-based models into platforms for predicting and evaluating policy responses to real world challenges around the world. It began with the observation that social science theories of human behavior are often used to estimate the consequences of alternative policy responses to important issues and challenges. However, alternative theories that remain subject to contradictory claims are ill suited to inform policy. The vision behind the DARPA project was to mine the social sciences literature for alternative theories of human behavior, and then formalize, instantiate, and integrate them within the context of an agent-based modeling system. The research team developed an experimental platform to evaluate the conditions under which alternative theories and groups of theories applied. The end result was a proof of concept developed from the ground up of social knowledge that could be used as an informative guide for policy analysis. This book describes in detail the process of designing and implementing a pilot system that helped DARPA assess the feasibility of a computational social science project on a large scale.

This book presents a unified framework, based on specialized evolutionary algorithms, for the global induction of various types of classification and regression trees from data. The resulting univariate or oblique trees are significantly smaller than those produced by standard top-down methods, an aspect that is critical for the interpretation of mined patterns by domain analysts. The approach presented here is extremely flexible and can easily be adapted to specific data mining applications, e.g. cost-sensitive model trees for financial data or multi-test trees for gene expression data. The global induction can be efficiently applied to large-scale data without the need for extraordinary resources. With a simple GPU-based acceleration, datasets composed of millions of instances can be mined in minutes. In the event that the size of the datasets makes the fastest memory computing impossible, the Spark-based implementation on computer clusters, which offers impressive fault tolerance and scalability potential, can be applied.