This book aims to promote a sample of current theoretical and application oriented intelligent systems research specifically in the field of neural networks computing. It presents examples of experimental and real-world investigations that demonstrate contemporary achievements and advances in the area of intelligent systems. This book will prove as a valuable source of up-to-date theoretical and application oriented research in intelligent systems for researchers and postgraduate students.

The Intelligent Techniques for Planning presents a number of modern approaches to the area of automated planning. These approaches combine methods from classical planning such as the construction of graphs and the use of domain-independent heuristics with techniques from other areas of artificial intelligence. This book discuses, in detail, a number of state-of-the-art planning systems that utilize constraint satisfaction techniques in order to deal with time and resources, machine learning in order to utilize experience drawn from past runs, methods from knowledge systems for more expressive representation of knowledge and ideas from other areas such as Intelligent Agents. Apart from the thorough analysis and implementation details, each chapter of the book also provides extensive background information about its subject and presents and comments on similar approaches done in the past.

This book presents the scientific outcome of the 5th International Conference on Applied Computing and Information Technology (ACIT 2017), which was held on July 9-13, 2017 in Hamamatsu, Japan. The aim of this conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the numerous fields of computer science, to share their experiences and to exchange new ideas and information in a meaningful way. The book includes research findings on all aspects (theory, applications and tools) of computer and information science, and discusses the practical challenges encountered along the way and the solutions adopted to solve them. This book features 12 of the conference's most promising papers, written by authors who are expected to make important contributions to the field of computer and information science.

Condition Monitoring Using Computational Intelligence Methods promotes the various approaches gathered under the umbrella of computational intelligence to show how condition monitoring can be used to avoid equipment failures and lengthen its useful life, minimize downtime and reduce maintenance costs. The text introduces various signal-processing and pre-processing techniques, wavelets and principal component analysis, for example, together with their uses in condition monitoring and details the development of effective feature extraction techniques classified into frequency-, time-frequency- and time-domain analysis. Data generated by these techniques can then be used for condition classification employing tools such as: * fuzzy systems; rough and neuro-rough sets; neural and Bayesian networks;hidden Markov and Gaussian mixture models; and support vector machines.

This book is the very first book-length study devoted to the advances in technological development and systems research in cooperative economics. The chapters provide, first of all, a coherent framework for understanding and applying the concepts and approaches of complexity and systems science for the advanced study of cooperative networks and particular cooperative enterprises and communities. Second, the book serves as a unique source of reliable information on the frontier information technologies available for the production, consumer, credit, and agricultural cooperative enterprises, discussing predominant strategies, potential drivers of change, and responses to complex problems. Given the diverse range of backgrounds and advanced research results, researchers, decision-makers, and stakeholders from all fields of cooperative economics in any country of the world will undoubtedly benefit from this book.

In this volume, first we formulate a framework of fuzzy types to represent both partial truth and uncertainty about concept and relation types in conceptual graphs. Like fuzzy attribute values, fuzzy types also form a lattice laying a common ground for lattice-based computation of fuzzy granules. Second, for automated reasoning with fuzzy conceptual graphs, we develop foundations of order-sorted fuzzy set logic programming, extending the theory of annotated logic programs of Kifer and Subrahmanian (1992). Third, we show some recent applications of fuzzy conceptual graphs to modelling and computing with generally quantified statements, approximate knowledge retrieval, and natural language query understanding.

The integrated and advanced science research topic man-machine-environment system engineering (MMESE) was first established in China by Professor Shengzhao Long in 1981, with direct support from one of the greatest modern Chinese scientists, Xuesen Qian. In a letter to Shengzhao Long from October 22nd, 1993, Xuesen Qian wrote: "You have created a very important modern science and technology in China!" MMESE primarily focuses on the relationship between man, machines and the environment, studying the optimum combination of man-machine-environment systems. In this system, "man" refers to people in the workplace (e.g. operators, decision-makers); " machine" is the general name for any object controlled by man (including tools, machinery, computers, systems and technologies), and "environment" describes the specific working conditions under which man and machine interact (e.g. temperature, noise, vibration, hazardous gases etc.). The three goals of optimization of man-machine-environment systems are to ensure safety, efficiency and economy. Proceedings of the 14th International Conference on Man-Machine-Environment System Engineering are an academic showcase of the best papers selected from more than 400 submissions, introducing readers to the top research topics and the latest developmental trends in the theory and application of MMESE. These proceedings are interdisciplinary studies on the concepts and methods of physiology, psychology, system engineering, computer science, environment science, management, education, and other related disciplines. Researchers and professionals working in these interdisciplinary fields and researchers on MMESE related topics will benefit from these proceedings.

Noisy optimization is a topic of growing interest for researchers working on mainstream optimization problems. Although several techniques for dealing with stochastic noise in optimization problems are covered in journals and conference proceedings, today there are virtually no books that approach noisy optimization from a layman's perspective; this book remedies that gap. Beginning with the foundations of evolutionary optimization, the book subsequently explores the principles of noisy optimization in single and multi-objective settings, and presents detailed illustrations of the principles developed for application in real-world multi-agent coordination problems. Special emphasis is given to the design of intelligent algorithms for noisy optimization in real-time applications. The book is unique in terms of its content, writing style and above all its simplicity, which will appeal to readers with a broad range of backgrounds. The book is divided into 7 chapters, the first of which provides an introduction to Swarm and Evolutionary Optimization algorithms. Chapter 2 includes a thorough review of agent architectures for multi-agent coordination. In turn, Chapter 3 provides an extensive review of noisy optimization, while Chapter 4 addresses issues of noise handling in the context of single-objective optimization problems. An illustrative case study on multi-robot path-planning in the presence of measurement noise is also highlighted in this chapter. Chapter 5 deals with noisy multi-objective optimization and includes a case study on noisy multi-robot box-pushing. In Chapter 6, the authors examine the scope of various algorithms in noisy optimization problems. Lastly, Chapter 7 summarizes the main results obtained in the previous chapters and elaborates on the book's potential with regard to real-world noisy optimization problems.

Computational Intelligence (CI) has emerged as a rapid growing field over the past decade. Its various techniques have been recognized as powerful tools for intelligent information processing, decision making and knowledge management.

"Advances of Computational Intelligence in Industrial Systems" reports the exploration of CI frontiers with an emphasis on a broad spectrum of real-world applications. Section I Theory and Foundation presents some of the latest developments in CI, e.g. particle swarm optimization, Web services, data mining with privacy protection, kernel methods for text analysis, etc. Section II Industrial Application covers the CI applications in a wide variety of domains, e.g. clinical decision support, process monitoring for industrial CNC machine, novelty detection for jet engines, ant algorithm for berth allocation, etc.

Such a collection of chapters has presented the state-of-the-art of CI applications in industry and will be an essential resource for professionals and researchers who wish to learn and spot the opportunities in applying CI techniques to their particular problems. "

This book gathers the contributions presented at the 4th International KES Conference on Smart Education and Smart e-Learning (KES-SEEL-17), which took place in Vilamoura, Algarve, Portugal, June 21-23, 2017. Smart education and smart e-Learning are emerging and rapidly growing areas. They represent the innovative integration of smart systems, technologies and objects, smart environments, smart pedagogy, smart learning and academic analytics, various branches of computer science and computer engineering, and state-of-the-art smart educational software and/or hardware systems. It contains a total of 48 peer-reviewed book chapters that are grouped into several parts: Part 1 - Smart Pedagogy, Part 2 - Smart e-Learning, Part 3 - Systems and Technologies for Smart Education, Part 4 - Smart Teaching, and Part 5 - Smart Education: National Initiatives and Approaches. The book offers a valuable source of research data, information on best practices, and case studies for educators, researchers, Ph.D. students, administrators, and practitioners-and all those who are interested in innovative areas of smart education and smart e-Learning.

The increasing complexity of our world demands new perspectives on the role of technology in decision making. Human decision making has its li- tations in terms of information-processing capacity. We need new technology to cope with the increasingly complex and information-rich nature of our modern society. This is particularly true for critical environments such as crisis management and tra?c management, where humans need to engage in close collaborations with arti?cial systems to observe and understand the situation and respond in a sensible way. We believe that close collaborations between humans and arti?cial systems will become essential and that the importance of research into Interactive Collaborative Information Systems (ICIS) is self-evident. Developments in information and communication technology have ra- cally changed our working environments. The vast amount of information available nowadays and the wirelessly networked nature of our modern so- ety open up new opportunities to handle di?cult decision-making situations such as computer-supported situation assessment and distributed decision making. To make good use of these new possibilities, we need to update our traditional views on the role and capabilities of information systems. The aim of the Interactive Collaborative Information Systems project is to develop techniques that support humans in complex information en- ronments and that facilitate distributed decision-making capabilities. ICIS emphasizes the importance of building actor-agent communities: close c- laborations between human and arti?cial actors that highlight their comp- mentary capabilities, and in which task distribution is ?exible and adaptive.

Cutting-edge developments in artificial intelligence are now driving applications that are only hinting at the level of value they will soon contribute to organizations, consumers, and societies across all domains.""Distributed Artificial Intelligence, Agent Technology, and Collaborative Applications"" offers an enriched set of research articles in artificial intelligence (AI), covering significant AI subjects such as information retrieval, conceptual modeling, supply chain demand forecasting, and machine learning algorithms. This comprehensive collection provides libraries with a one-stop resource to equip the academic, industrial, and managerial communities with an in-depth look into the most pertinent AI advances that will lead to the most valuable applications.

The goal of this book is to establish the foundation, principles, theory, and concepts that are the backbone of real, autonomous Artificial Intelligence. Presented here are some basic human intelligence concepts framed for Artificial Intelligence systems. These include concepts like Metacognition and Metamemory, along with architectural constructs for Artificial Intelligence versions of human brain functions like the prefrontal cortex. Also presented are possible hardware and software architectures that lend themselves to learning, reasoning, and self-evolution

This important text/reference presents state-of-the-art research on intelligent vehicles, covering not only topics of object/obstacle detection and recognition, but also aspects of vehicle motion control. With an emphasis on both high-level concepts, and practical detail, the text links theory, algorithms, and issues of hardware and software implementation in intelligent vehicle research. Topics and features: presents a thorough introduction to the development and latest progress in intelligent vehicle research, and proposes a basic framework; provides detection and tracking algorithms for structured and unstructured roads, as well as on-road vehicle detection and tracking algorithms using boosted Gabor features; discusses an approach for multiple sensor-based multiple-object tracking, in addition to an integrated DGPS/IMU positioning approach; examines a vehicle navigation approach using global views; introduces algorithms for lateral and longitudinal vehicle motion control.

This book highlights recent advances in the design of hybrid intelligent systems based on nature-inspired optimization and their application in areas such as intelligent control and robotics, pattern recognition, time series prediction, and optimization of complex problems. The book is divided into seven main parts, the first of which addresses theoretical aspects of and new concepts and algorithms based on type-2 and intuitionistic fuzzy logic systems. The second part focuses on neural network theory, and explores the applications of neural networks in diverse areas, such as time series prediction and pattern recognition. The book's third part presents enhancements to meta-heuristics based on fuzzy logic techniques and describes new nature-inspired optimization algorithms that employ fuzzy dynamic adaptation of parameters, while the fourth part presents diverse applications of nature-inspired optimization algorithms. In turn, the fifth part investigates applications of fuzzy logic in diverse areas, such as time series prediction and pattern recognition. The sixth part examines new optimization algorithms and their applications. Lastly, the seventh part is dedicated to the design and application of different hybrid intelligent systems.

The primary goal of this book is the specification, design and testing of an inertially stabilized camera platform for assistance systems with the focus on adaptive inertial measurement. This can be divided into sub-goals which also served as internal milestones for the project; development of a highly miniaturized inertial measurement unit, development of adaptive control algorithms for gaze stabilization, industrial application and development of multi-sensor fusion algorithms.

Although parallel robots are known to offer many advantages with respect to accuracy, dynamics, and stiffness, major breakthroughs in industrial applications have not yet taken place. This is due to a knowledge gap preventing fast and precise execution of industrial handling and assembly tasks. This book focuses on the design, modeling, and control of innovative parallel structures as well as the integration of novel machine elements. Special attention is paid to the integration of active components into lightweight links and passive joints. In addition, new control concepts are introduced to minimize structural vibrations. Although the optimization of robot systems itself allows a reduction of cycle times, these can be further decreased by improved path planning, robot programming, and automated assembly planning concepts described by 25 contributions within this book. The content of this volume is subdivided into four main parts dealing with Modeling and Design, System Implementation, Control and Programming as well as Adaptronics and Components. This book is aimed at researchers and postgraduates working in the field of parallel robots as well as practicing engineers dealing with industrial robot development and robotic applications.

This book will be the first to bring together research material from different communities, Computer Science and especially Artificial Intelligence, and Social Sciences, e.g. Anthropology, Social Psychology, Political Science that present ideas and viewpoints, methods and models on inter-cultural collaboration and negotiation.

With increasing globalization of business and science, cultural differences of the parties are an important factor that affects the process and outcomes of collaborative and self-interested interactions. The social science literature on culture as well as human collaboration and negotiation is vast. Most of this literature is devoted to work within the same culture. Artificial intelligence researchers, on the other hand, have developed computational models of cooperation, conflict resolution and negotiation, but paying almost no attention to identifying and modeling cultural factors. In recent years, we have witnessed a great increase in interest in understanding inter-cultural interactions. This has led to increased interest of social scientists and computational scientists in theoretical and experimental analysis of inter-cultural exchanges, modeling and support. Currently, these communities are largely unconnected. There is a great need to bring them together to share research work and experiences, discuss ideas and forge interdisciplinary collaborative relations.

The book will be of interest to researchers from AI/computer science and social/behavioral sciences fields, such as psychology, sociology, communications, organizational science.

The papers in this volume comprise the refereed proceedings of the conference Arti- cial Intelligence in Theory and Practice (IFIP AI 2010), which formed part of the 21st World Computer Congress of IFIP, the International Federation for Information Pr- essing (WCC-2010), in Brisbane, Australia in September 2010. The conference was organized by the IFIP Technical Committee on Artificial Int- ligence (Technical Committee 12) and its Working Group 12.5 (Artificial Intelligence Applications). All papers were reviewed by at least two members of our Program Committee. - nal decisions were made by the Executive Program Committee, which comprised John Debenham (University of Technology, Sydney, Australia), Ilias Maglogiannis (University of Central Greece, Lamia, Greece), Eunika Mercier-Laurent (KIM, France) and myself. The best papers were selected for the conference, either as long papers (maximum 10 pages) or as short papers (maximum 5 pages) and are included in this volume. The international nature of IFIP is amply reflected in the large number of countries represented here. I should like to thank the Conference Chair, Tharam Dillon, for all his efforts and the members of our Program Committee for reviewing papers under a very tight de- line.

A diverse international set of authors discuss Artificial/Computational Sapience and Sapient Systems in this unique and useful volume. The reader is guided through the subject in a structured and comprehensive manner that begins with chapters discussing philosophical, historical, and semiotic ideas about what properties are expected from Sapient (Wise) systems. Following that, chapters describe mathematical and engineering views on sapience, relating these to philosophical, semiotic, cognitive, and neuro-biological perspectives.

Complex Automated Negotiations have been widely studied and are becoming an important, emerging area in the field of Autonomous Agents and Multi-Agent Systems. In general, automated negotiations can be complex, since there are a lot of factors that characterize such negotiations. These factors include the number of issues, dependency between issues, representation of utility, negotiation protocol, negotiation form (bilateral or multi-party), time constraints, etc. Software agents can support automation or simulation of such complex negotiations on the behalf of their owners, and can provide them with adequate bargaining strategies. In many multi-issue bargaining settings, negotiation becomes more than a zero-sum game, so bargaining agents have an incentive to cooperate in order to achieve efficient win-win agreements. Also, in a complex negotiation, there could be multiple issues that are interdependent. Thus, agent's utility will become more complex than simple utility functions. Further, negotiation forms and protocols could be different between bilateral situations and multi-party situations. To realize such a complex automated negotiati on, we have to incorporate advanced Artificial Intelligence technologies includes search, CSP, graphical utility models, Bays nets, auctions, utility graphs, predicting and learning methods. Applications could include e-commerce tools, decisionmaking support tools, negotiation support tools, collaboration tools, etc.

These issues are explored by researchers from different communities in Autonomous Agents and Multi-Agent systems. They are, for instance, being studied in agent negotiation, multi-issue negotiations, auctions, mechanism design, electronic commerce, voting, secure protocols, matchmaking & brokering, argumentation, and co-operation mechanisms. This book is also edited from some aspects of negotiation researches including theoretical mechanism design of trading based on auctions, allocation mechanism based on negotiation among multi-agent, case-study and analysis of automated negotiations, data engineering issues in negotiations, and so on.

The authors have consolidated their research work in this volume titled Soft Computing for Data Mining Applications. The monograph gives an insight into the research in the ?elds of Data Mining in combination with Soft Computing methodologies. In these days, the data continues to grow - ponentially. Much of the data is implicitly or explicitly imprecise. Database discovery seeks to discover noteworthy, unrecognized associations between the data items in the existing database. The potential of discovery comes from the realization that alternate contexts may reveal additional valuable information. The rate at which the data is storedis growing at a phenomenal rate. Asaresult, traditionaladhocmixturesofstatisticaltechniquesanddata managementtools are no longer adequate for analyzing this vast collection of data. Severaldomainswherelargevolumesofdataarestoredincentralizedor distributeddatabasesincludesapplicationslikeinelectroniccommerce, bio- formatics, computer security, Web intelligence, intelligent learning database systems, ?nance, marketing, healthcare, telecommunications, andother?elds. E?cient tools and algorithms for knowledge discovery in large data sets have been devised during the recent years. These methods exploit the ca- bility of computers to search huge amounts of data in a fast and e?ective manner. However, the data to be analyzed is imprecise and a?icted with - certainty. In the case of heterogeneous data sources such as text and video, the data might moreover be ambiguous and partly con?icting. Besides, p- terns and relationships of interest are usually approximate. Thus, in order to make the information mining process more robust it requires tolerance toward imprecision, uncertainty and exc

This book is mainly focused on two themes: transportation and smart city applications. Open geospatial science and technology is an increasingly important paradigm that offers the opportunity to promote the democratization of geographical information, the transparency of governments and institutions, as well as social, economic and urban opportunities. During the past decade, developments in the area of open geospatial data have greatly increased. The open source GIS research community believes that combining free and open software, open data, as well as open standards, leads to the creation of a sustainable ecosystem for accelerating new discoveries to help solve global cross-disciplinary urban challenges. The vision of this book is to enrich the existing literature on this topic, and act one step towards more sustainable cities through employment of open source GIS solutions that are reproducible. Various contributions are provided and practically implemented in several urban use cases. Therefore, apart from researchers, lecturers and students in the geography/urbanism domain, crowdsourcing and VGI domain, as well as open source GIS domain, it is believed the specialists and mentors in municipalities and urban planning departments as well as professionals in private companies would be interested to read this book.

Data Management is the process of planning, coordinating and controlling data resources. More often, applications need to store and search a large amount of data. Managing Data has been continuously challenged by demands from various areas and applications and has evolved in parallel with advances in hardware and computing techniques.

This volume focuses on its recent advances and it is composed of five parts and a total of eighteen chapters. The first part of the book contains five contributions in the area of information retrieval and Web intelligence: a novel approach to solving index selection problem, integrated retrieval from Web of documents and data, bipolarity in database querying, deriving data summarization through ontologies, and granular computing for Web intelligence. The second part of the book contains four contributions in knowledge discovery area. Its third part contains three contributions in information integration and data security area. The remaining two parts of the book contain six contributions in the area of intelligent agents and applications of data management in medical domain.