Castel Ivano, originally built in 1375, is one of many beautiful and impressive castles strategically placed atop hills in Trentino's Valsugana in Northern Italy. It was in this castle on a series of brilliant sunny crisp November days in 1990 that an international group of computer scientists and cognitive scientists met at a workshop to discuss theoretical and applied issues concerning communi cation from an Artificial Intelligence and Cognitive Science perspective. About forty people, representing nine countries, participated in the workshop, either as speakers, discussants, or observers. The main motivationfor the workshop wasto address the questionofwhether and how current computational approaches to communication can or might be able to accommodate the range of complexities that characterize both human human and human-machine communication. The chapters in this book are based on the papers that were presented at the workshop. They are presented in an order that is determined primarily by the specificity of the topics they address. The initial chapters are more theoretical in nature with an emphasis on formal approaches to communication. The middle chapters focus on particular application issues, such as the generation ofmultimedia documents and the role of planning in building systems to support human-human or human-machine interaction. The final few chapters consider more general issues relating to com munication, such as the influence ofsocial structure on, and the role of affect in communication."

The microelectronics market, with special emphasis to the production of complex mixed-signal systems-on-chip (SoC), is driven by three main dynamics, time-- market, productivity and managing complexity. Pushed by the progress in na- meter technology, the design teams are facing a curve of complexity that grows exponentially, thereby slowing down the productivity design rate. Analog design automation tools are not developing at the same pace of technology, once custom design, characterized by decisions taken at each step of the analog design flow, - lies most of the time on designer knowledge and expertise. Actually, the use of - sign management platforms, like the Cadences Virtuoso platform, with a set of - tegrated CAD tools and database facilities to deal with the design transformations from the system level to the physical implementation, can significantly speed-up the design process and enhance the productivity of analog/mixed-signal integrated circuit (IC) design teams. These design management platforms are a valuable help in analog IC design but they are still far behind the development stage of design automation tools already available for digital design. Therefore, the development of new CAD tools and design methodologies for analog and mixed-signal ICs is ess- tial to increase the designer's productivity and reduce design productivitygap. The work presented in this book describes a new design automation approach to the problem of sizing analog ICs.

This book offers a widely interdisciplinary approach to investigating important questions surrounding the cognitive foundations of group attitudes and social interaction. The volume tackles issues such as the relationship between individual and group attitudes, the cognitive bases of group identity and group identification and the link between emotions and individual attitudes. This volume delves into the links between individual attitudes (such as beliefs, goals and intentions) and how they are reflected in shared attitudes where common belief, collective acceptance, joint intentions, and group preferences come into play. It pursues answers to the connections between trust and beliefs, goals and intentions and attempts to investigate questions such as: does trust have an affective component and how it may relate to hope and fear? The volume also scrutinizes game theory and questions whether it can satisfactorily explain and model social interaction and if there may be any concepts which are not addressed by the current theory. Contributors are derived from disciplines including philosophy, economics, psychology, logic and computer science. Interdisciplinary in scope and comprehensive detail, this volume integrates a variety of approaches - philosophical, psychological and artificial intelligence - to strategic, normative and emotional aspects of social interaction.

The extended and revised second edition of this successful monograph presents advanced modeling, analysis and control techniques of Flexible AC Transmission Systems (FACTS). The book covers comprehensively a range of power-system control problems: from steady-state voltage and power flow control, to voltage and reactive power control, to voltage stability control, to small signal stability control using FACTS controllers.

In the six years since the first edition of the book has been published research on the FACTS has continued to flourish while renewable energy has developed into a mature and booming global green business. The second edition reflects the new developments in converter configuration, smart grid technologies, super power grid developments worldwide, new approaches for FACTS control design, new controllers for distribution system control, and power electronic controllers in wind generation operation and control. The latest trends of VSC-HVDC with multilevel architecture have been included and four completely new chapters have been added devoted to Multi-Agent Systems for Coordinated Control of FACTS-devices, Power System Stability Control using FACTS with Multiple Operating Points, Control of a Looping Device in a Distribution System, and Power Electronic Control for Wind Generation.

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The purpose of the book is to advance in the understanding of brain function by defining a general framework for representation based on category theory. The idea is to bring this mathematical formalism into the domain of neural representation of physical spaces, setting the basis for a theory of mental representation, able to relate empirical findings, uniting them into a sound theoretical corpus.

The innovative approach presented in the book provides a horizon of interdisciplinary collaboration that aims to set up a common agenda that synthesizes mathematical formalization and empirical procedures in a systemic way. Category theory has been successfully applied to qualitative analysis, mainly in theoretical computer science to deal with programming language semantics. Nevertheless, the potential of category theoretic tools for quantitative analysis of networks has not been tackled so far. Statistical methods to investigate graph structure typically rely on network parameters. Category theory can be seen as an abstraction of graph theory. Thus, new categorical properties can be added into network analysis and graph theoretic constructs can be accordingly extended in more fundamental basis. By generalizing networks using category theory we can address questions and elaborate answers in a more fundamental way without waiving graph theoretic tools. The vital issue is to establish a new framework for quantitative analysis of networks using the theory of categories, in which computational neuroscientists and network theorists may tackle in more efficient ways the dynamics of brain cognitive networks.

The intended audience of the book is researchers who wish to explore the validity of mathematical principles in the understanding of cognitive systems. All the actors in cognitive science: philosophers, engineers, neurobiologists, cognitive psychologists, computer scientists etc. are akin to discover along its pages new unforeseen connections through the development of concepts and formal theories described in the book. Practitioners of both pure and applied mathematics e.g., network theorists, will be delighted with the mapping of abstract mathematical concepts in the terra incognita of cognition.

Soft Computing today is a very vast field whose extent is beyond measure. The boundaries of this magnificent field are spreading at an enormous rate making it possible to build computationally intelligent systems that can do virtually anything, even after considering the hostile practical limitations. Soft Computing, mainly comprising of Artificial Neural Networks, Evolutionary Computation, and Fuzzy Logic may itself be insufficient to cater to the needs of various kinds of complex problems. In such a scenario, we need to carry out amalgamation of same or different computing approaches, along with heuristics, to make fabulous systems for problem solving. There is further an attempt to make these computing systems as adaptable as possible, where the value of any parameter is set and continuously modified by the system itself. This book first presents the basic computing techniques, draws special attention towards their advantages and disadvantages, and then motivates their fusion, in a manner to maximize the advantages and minimize the disadvantages. Conceptualization is a key element of the book, where emphasis is on visualizing the dynamics going inside the technique of use, and hence noting the shortcomings. A detailed description of different varieties of hybrid and adaptive computing systems is given, paying special attention towards conceptualization and motivation. Different evolutionary techniques are discussed that hold potential for generation of fairly complex systems. The complete book is supported by the application of these techniques to biometrics. This not only enables better understanding of the techniques with the added application base, it also opens new dimensions of possibilities how multiple biometric modalities can be fused together to make effective and scalable systems.

The coupling of models from different physical domains and the efficient and reliable simulation of multidisciplinary problems in engineering applications are important topics for various fields of engineering, in simulation technology and in the development and analysis of numerical solvers.

The volume presents advanced modelling and simulation techniques for the dynamical analysis of coupled engineering systems consisting of mechanical, electrical, hydraulic and biological components as well as control devices often based on computer hardware and software. The book starts with some basics in multibody dynamics and in port-based modelling and focuses on the modelling and simulation of heterogeneous systems with special emphasis on robust and efficient numerical solution techniques and on a variety of applied problems including case studies of co-simulation in industrial applications, methods and problems of model based controller design and real-time application.

Hybrid Optimization focuses on the application of artificial intelligence and operations research techniques to constraint programming for solving combinatorial optimization problems. This book covers the most relevant topics investigated in the last ten years by leading experts in the field, and speculates about future directions for research.

This book includes contributions by experts from different but related areas of research including constraint programming, decision theory, operations research, SAT, artificial intelligence, as well as others. These diverse perspectives are actively combined and contrasted in order to evaluate their relative advantages.

This volume presents techniques for hybrid modeling, integrated solving strategies including global constraints, decomposition techniques, use of relaxations, and search strategies including tree search local search and metaheuristics. Various applications of the techniques presented as well as supplementary computational tools are also discussed.

This book presents the combined peer-reviewed proceedings of the tenth International Symposium on Intelligent Distributed Computing (IDC'2016), which was held in Paris, France from October 10th to 12th, 2016. The 23 contributions address a range of topics related to theory and application of intelligent distributed computing, including: Intelligent Distributed Agent-Based Systems, Ambient Intelligence and Social Networks, Computational Sustainability, Intelligent Distributed Knowledge Representation and Processing, Smart Networks, Networked Intelligence and Intelligent Distributed Applications, amongst others.

Chaos-based cryptography, attracting many researchers in the past decade, is a research field across two fields, i.e., chaos (nonlinear dynamic system) and cryptography (computer and data security). It Chaos' properties, such as randomness and ergodicity, have been proved to be suitable for designing the means for data protection. The book gives a thorough description of chaos-based cryptography, which consists of chaos basic theory, chaos properties suitable for cryptography, chaos-based cryptographic techniques, and various secure applications based on chaos. Additionally, it covers both the latest research results and some open issues or hot topics. The book creates a collection of high-quality chapters contributed by leading experts in the related fields. It embraces a wide variety of aspects of the related subject areas and provide a scientifically and scholarly sound treatment of state-of-the-art techniques to students, researchers, academics, personnel of law enforcement and IT practitioners who are interested or involved in the study, research, use, design and development of techniques related to chaos-based cryptography.

The book is a compilation of high-quality scientific papers presented at the 3rd International Conference on Computer & Communication Technologies (IC3T 2016). The individual papers address cutting-edge technologies and applications of soft computing, artificial intelligence and communication. In addition, a variety of further topics are discussed, which include data mining, machine intelligence, fuzzy computing, sensor networks, signal and image processing, human-computer interaction, web intelligence, etc. As such, it offers readers a valuable and unique resource.

One of the attractions of fuzzy logic is its utility in solving many real engineering problems. As many have realised, the major obstacles in building a real intelligent machine involve dealing with random disturbances, processing large amounts of imprecise data, interacting with a dynamically changing environment, and coping with uncertainty. Neural-fuzzy techniques help one to solve many of these problems. Fuzzy Logic and Intelligent Systems reflects the most recent developments in neural networks and fuzzy logic, and their application in intelligent systems. In addition, the balance between theoretical work and applications makes the book suitable for both researchers and engineers, as well as for graduate students.

Modern theories of brain function are increasingly concerned with dynamics. The task of organizing perception and behaviour in a meaningful interaction with the external world prompts the brain to recruit its various resources in a properly coordinated manner. Vis-a-vis the complexity and multitude of the dynamics involved, a careful orchestration of the various processing components, distributed over space and time, is essential. Hence, it should come as no surprise that a number of recent developments in both experimental and theoretical brain science have emphasized the aspect of spatio-temporal coordination.

This collection of papers intends to capture these various developments in the brain sciences. It brings together new insights and concepts from various branches of experimental and theoretical neuroscience, partly in the form of review chapters, partly in short, focussed contributions, or critical essays. Further it sets out to explore the problems of the processing of the temporal dimension of sensory input and of the generation of space-time patterns in the motor output, as well as the intervening storage and transformation of temporal patterns in nerve nets.

The publication is divided into four major sections: the first considers spatio-temporal aspects of brain function in the context of processing of sensory input and perception and the third, spatio-temporal aspects of brain function at the output end: planning and control of movement. The second section is dedicated to the intervening level of neuronal activity in the working brain and the various dynamics observed at different levels of resolution in space and time. The fourth part combines contributions that transcend this scheme.

It is hoped the book achieves its goal which is to raise an interest in theoretical models that actively seek confrontation with experimental data from the functioning brain, and by a didactic effort aimed at experimentalists to present their data in a format that makes them more amenable to theory.

The field of Intelligent Systems has expanded enormously during the last two decades with many theoretical and practical results already available, which are the outcome of the synergetic merging of classical fields such as system theory, artificial intelligence, information theory, soft computing, operations research, linguistic theory and others. This book presents a collection of timely contributions that cover a wide, well-selected range of topics within the field. The book contains forty-seven contributions with an emphasis on computational and processing issues. The book is structured in four parts, as follows: Part I: Computer-aided intelligent systems and tools; Part II: Information extraction from texts, natural language interfaces and intelligent retrieval systems; Part III: Image processing and video-based systems; Part IV: Applications Particular topics treated include: planning; problem solving; information extraction from texts; natural language interfaces; audio retrieval systems; multi-agent systems; image compression, image and segmentation, and human face recognition. Applications include: peri-urban road network extraction; analysis of structures; climatic sensor signal analysis; aortic pressure assessment; hospital laboratory planning; fatigue analysis using electromyographic signals; forecasting in power systems. The book can serve as a reference pool of knowledge that may inspire and motivate researchers and practitioners for further developments and modern-day applications. The teacher and student in related postgraduate and research programs can thereby save considerable time in searching the scattered literature in the field.

Computational Intelligence is tolerant of imprecise information, partial truth and uncertainty. This book presents a selected collection of contributions on a focused treatment of important elements of CI, centred on its key element: learning. This book presents novel applications and real world applications working in Manufacturing and Engineering, and it sets a basis for understanding Domotic and Production Methods of the XXI Century.

Dexterous and autonomous manipulation is a key technology for the personal and service robots of the future. Advances in Bimanual Manipulation edited by Bruno Siciliano provides the robotics community with the most noticeable results of the four-year European project DEXMART (DEXterous and autonomous dual-arm hand robotic manipulation with sMART sensory-motor skills: A bridge from natural to artificial cognition). The volume covers a host of highly important topics in the field, concerned with modelling and learning of human manipulation skills, algorithms for task planning, human-robot interaction, and grasping, as well as hardware design of dexterous anthropomorphic hands. The results described in this five-chapter collection are believed to pave the way towards the development of robotic systems endowed with dexterous and human-aware dual-arm/hand manipulation skills for objects, operating with a high degree of autonomy in unstructured real-world environments.

In this book, internationally recognized experts in philosophy of science, computer science, and modeling and simulation are contributing to the discussion on how ontology, epistemology, and teleology will contribute to enable the next generation of intelligent modeling and simulation applications. It is well understood that a simulation can provide the technical means to display the behavior of a system over time, including following observed trends to predict future possible states, but how reliable and trustworthy are such predictions? The questions about what we can know (ontology), how we gain new knowledge (epistemology), and what we do with this knowledge (teleology) are therefore illuminated from these very different perspectives, as each experts uses a different facet to look at these challenges. The result of bringing these perspectives into one book is a challenging compendium that gives room for a spectrum of challenges: from general philosophy questions, such as can we use modeling and simulation and other computational means at all to discover new knowledge, down to computational methods to improve semantic interoperability between systems or methods addressing how to apply the recent insights of service oriented approaches to support distributed artificial intelligence. As such, this book has been compiled as an entry point to new domains for students, scholars, and practitioners and to raise the curiosity in them to learn more to fully address the topics of ontology, epistemology, and teleology from philosophical, computational, and conceptual viewpoints.

Bioinspired computation methods such as evolutionary algorithms and ant colony optimization are being applied successfully to complex engineering problems and to problems from combinatorial optimization, and with this comes the requirement to more fully understand the computational complexity of these search heuristics. This is the first textbook covering the most important results achieved in this area.

The authors study the computational complexity of bioinspired computation and show how runtime behavior can be analyzed in a rigorous way using some of the best-known combinatorial optimization problems -- minimum spanning trees, shortest paths, maximum matching, covering and scheduling problems. A feature of the book is the separate treatment of single- and multiobjective problems, the latter a domain where the development of the underlying theory seems to be lagging practical successes.

This book will be very valuable for teaching courses on bioinspired computation and combinatorial optimization. Researchers will also benefit as the presentation of the theory covers the most important developments in the field over the last 10 years. Finally, with a focus on well-studied combinatorial optimization problems rather than toy problems, the book will also be very valuable for practitioners in this field.

This book describes approaches to solving the problems of developing the central nervous system of robots (CNSR) based on smart electromechanical systems (SEMS) modules, principles of construction of the various modules of the central nervous system and variants of mathematical software CNSR in control systems for intelligent robots. It presents the latest advances in theory and practice at the Russian Academy of Sciences. Developers of intelligent robots to solve modern problems in robotics are increasingly addressing the use of the bionic approach to create robots that mimic the complexity and adaptability of biological systems. These have smart electromechanical system (SEMS), which are used in various cyber-physical systems (CPhS), and allow the functions of calculation, control, communications, information storage, monitoring, measurement and control of parameters and environmental parameters to be integrated. The behavior of such systems is based on the information received from the central nervous system of the robot (CNSR) on the state of the environment and system state. Recent advances in computer science, measuring and computing techniques have stimulated the practical realization of the CNSR, providing a fundamentally new approach to the methods and algorithms of formation of appropriate robot behavior. Intelligent robots with CNSR occupy a special place among the highly efficient robotic systems with parallel structures and play an important role in modern automated industries, and this timely book is a valuable resource for specialists in the field of robotics and control, as well as for students majoring in "Robots", "System analysis and management", and "Automation and control".

The modern origin of fuzzy sets, fuzzy algebra, fuzzy decision making, and "computing with words" is conventionally traced to Lotfi Zadeh's publication in 1965 of his path-breaking refutation of binary set theory. In a sixteen-page article, modestly titled "Fuzzy Sets" and published in the journal Information and Control, Zadeh launched a multi-disciplinary revolution. The start was relatively slow, but momentum gathered quickly. From 1970 to 1979 there were about 500 journal publications with the word fuzzy in the title; from 2000 to 2009 there were more than 35,000. At present, citations to Zadeh's publications are running at a rate of about 1,500-2,000 per year, and this rate continues to rise. Almost all applications of Zadeh's ideas have been in highly technical scientific fields, not in the social sciences. Zadeh was surprised by this development. In a personal note he states: "When I wrote my l965 paper, I expected that fuzzy set theory would be applied primarily in the realm of human sciences. Contrary to my expectation, fuzzy set theory and fuzzy logic are applied in the main in physical and engineering sciences." In fact, the first comprehensive examination of fuzzy sets by a social scientist did not appear until 1987, a full twenty-two years after the publication of Zadeh's seminal article, when Michael Smithson, an Australian psychologist, published Fuzzy Set Analysis for Behavioral and Social Sciences.

The present book outlines a new approach to possibilistic clustering in which the sought clustering structure of the set of objects is based directly on the formal definition of fuzzy cluster and the possibilistic memberships are determined directly from the values of the pairwise similarity of objects. The proposed approach can be used for solving different classification problems. Here, some techniques that might be useful at this purpose are outlined, including a methodology for constructing a set of labeled objects for a semi-supervised clustering algorithm, a methodology for reducing analyzed attribute space dimensionality and a methods for asymmetric data processing. Moreover, a technique for constructing a subset of the most appropriate alternatives for a set of weak fuzzy preference relations, which are defined on a universe of alternatives, is described in detail, and a method for rapidly prototyping the Mamdani s fuzzy inference systems is introduced. This book addresses engineers, scientists, professors, students and post-graduate students, who are interested in and work with fuzzy clustering and its applications

Current Biomedical Databases are independently administered in geographically distinct locations, lending them almost ideally to adoption of intelligent data management approaches. This book focuses on research issues, problems and opportunities in Biomedical Data Infrastructure identifying new issues and directions for future research in Biomedical Data and Information Retrieval, Semantics in Biomedicine, and Biomedical Data Modeling and Analysis. The book will be a useful guide for researchers, practitioners, and graduate-level students interested in learning state-of-the-art development in biomedical data management.

During the past few years, data mining has grown rapidly in visibility and importance within information processing and decision analysis. This is par ticularly true in the realm of e-commerce, where data mining is moving from a "nice-to-have" to a "must-have" status. In a different though related context, a new computing methodology called granular computing is emerging as a powerful tool for the conception, analysis and design of information/intelligent systems. In essence, data mining deals with summarization of information which is resident in large data sets, while granular computing plays a key role in the summarization process by draw ing together points (objects) which are related through similarity, proximity or functionality. In this perspective, granular computing has a position of centrality in data mining. Another methodology which has high relevance to data mining and plays a central role in this volume is that of rough set theory. Basically, rough set theory may be viewed as a branch of granular computing. However, its applications to data mining have predated that of granular computing."