Search

Automatic content generation is the production of content for games, web pages, or other purposes by procedural means. Search-based automatic content generation employs search-based algorithms to accomplish automatic content generation. This book presents a number of different techniques for search-based automatic content generation where the search algorithm is an evolutionary algorithm. The chapters treat puzzle design, the creation of small maps or mazes, the use of L-systems and a generalization of L-system to create terrain maps, the use of cellular automata to create maps, and, finally, the decomposition of the design problem for large, complex maps culminating in the creation of a map for a fantasy game module with designersupplied content and tactical features. The evolutionary algorithms used for the different types of content are generic and similar, with the exception of the novel sparse initialization technique are presented in Chapter 2. The points where the content generation systems vary are in the design of their fitness functions and in the way the space of objects being searched is represented. A large variety of different fitness functions are designed and explained, and similarly radically different representations are applied to the design of digital objects all of which are, essentially, maps for use in games.

This book is a formalization of collected notes from an introductory game theory course taught at Queen's University. The course introduced traditional game theory and its formal analysis, but also moved to more modern approaches to game theory, providing a broad introduction to the current state of the discipline. Classical games, like the Prisoner's Dilemma and the Lady and the Tiger, are joined by a procedure for transforming mathematical games into card games. Included is an introduction and brief investigation into mathematical games, including combinatorial games such as Nim. The text examines techniques for creating tournaments, of the sort used in sports, and demonstrates how to obtain tournaments that are as fair as possible with regards to playing on courts. The tournaments are tested as in-class learning events, providing a novel curriculum item. Example tournaments are provided at the end of the book for instructors interested in running a tournament in their own classroom. The book is appropriate as a text or companion text for a one-semester course introducing the theory of games or for students who wish to get a sense of the scope and techniques of the field.

Evolving agents to play games is a promising technology. It can provide entertaining opponents for games like Chess or Checkers, matched to a human opponent as an alternative to the perfect and unbeatable opponents embodied by current artifical intelligences. Evolved agents also permit us to explore the strategy space of mathematical games like Prisoner's Dilemma and Rock-Paper-Scissors. This book summarizes, explores, and extends recent work showing that there are many unsuspected factors that must be controlled in order to create a plausible or useful set of agents for modeling cooperation and conflict, deal making, or other social behaviors. The book also provides a proposal for an agent training protocol that is intended as a step toward being able to train humaniform agents—in other words, agents that plausibly model human behavior.

Cooperation is pervasive throughout nature, but its origin remains an open question. For decades, social scientists, business leaders, and economists have struggled with an important question: why is cooperation so ubiquitous among unrelated humans? The answers would have profound effects because anything that promotes cooperation leads to more productive work environments and benefits society at large. Game theory provides an ideal framework for studying social dilemmas, or those situations in which people decide whether to cooperate with others (benefitting the group) or defect by prioritizing their self-interest (benefitting only the individual). The social dilemma is formulated as a mathematical game and then programmed into a computer model. Simulating the game allows researchers to investigate potential theories to explain how cooperation emerges and what promotes its persistence. Over the past 25 years, countless papers on social dilemma games have been published, yet arguably little progress has been made. The problem is the social dilemma game models are unrealistic in the sense they contain artificial constructs that deviate from the way humans act. This book describes the shortcomings in current social dilemma game modeling techniques and provides guidance on designing more effective models. A basic introduction to game theory is provided with an emphasis on the prisoner's dilemma, the most widely studied social dilemma game. Individual chapters are provided detailing the shortcomings of weak selection, spatial games, and the Moran process. Computer model validation is also discussed at length. The recommendations found in this book should help design more realistic social dilemma game models likely to produce a better understanding of human cooperation.

Games, whether educational or recreational, are meant to be fun. How do we ensure that the game delivers its intent? The answer to this question is playtesting. However, a haphazard playtest process cannot discover play experience from various dimensions. Players'perceptions, affordances, age, gender, culture, and many more human factors influence play experience. A playtest requires an intensive experimental process and scientific protocols to ensure that the outcomes seen are reliable for the designer. Playtesting and players'affordances are the focus of this book. This book is not just about the playtest procedures but also demonstrates how they lead to the conclusions obtained when considering data sets. The playtest process or playtest stories differ according to the hypothesis under investigation. We cover examples of playtesting to identify the impact of human factors, such as age and gender, to examine a player's preferences for game objects'design and colors. The book details topics to reflect on possible emotional outcomes of the player at the early stages of game design as well as the methodology for presenting questions to players in such a way as to elicit authentic feedback. This book is intended mainly for game designers, researchers, and developers. However, it provides a general understanding of affordances and human factors that can be informative for readers working in any domain.

The recent developments in wireless communications, networking, and embedded systems have driven various innovative Internet of Things (IoT) applications, e.g., smart cities, mobile healthcare, autonomous driving and drones. A common feature of these applications is the stringent requirements for low-latency communications. Considering the typical small payload size of IoT applications, it is of critical importance to reduce the size of the overhead message, e.g., identification information, pilot symbols for channel estimation, and control data. Such low-overhead communications also help to improve the energy efficiency of IoT devices. Recently, structured signal processing techniques have been introduced and developed to reduce the overheads for key design problems in IoT networks, such as channel estimation, device identification, and message decoding. By utilizing underlying system structures, including sparsity and low rank, these methods can achieve significant performance gains.This book provides an overview of four general structured signal processing models: a sparse linear model, a blind demixing model, a sparse blind demixing model, and a shuffled linear model, and discusses their applications in enabling low-overhead communications in IoT networks. Further, it presents practical algorithms based on both convex and nonconvex optimization approaches, as well as theoretical analyses that use various mathematical tools.

This book systematically introduces readers to the development of simulation models as well as the implementation and evaluation of simulation experiments with Tecnomatix Plant Simulation. Intended for all Plant Simulation users whose work involves complex tasks, it also offers an easy start for newcomers. Particular attention has been paid to introducing the simulation flow language SimTalk and its use in various aspects of simulation. In over 200 examples, the author demonstrates how to combine the blocks for simulation models and how to employ SimTalk in complex control and analysis tasks. The content ranges from a description of the basic functions of the material flow blocks to more advanced topics such as the implementation of database-supported warehouse control by using the SQLite interface, and the exchange of data using XML, ActiveX, COM or DDE.

This book includes a selection of papers presented at the Third World Conference on Qualitative Research (WCQR2018), held in Lisbon, Portugal on October 17–19, 2018. The WCQR2018 focused on four main fields of application (Education, Health, Social Sciences, and Engineering and Technology) and seven main subjects: Rationale and Paradigms of Qualitative Research; Systematization of Approaches with Qualitative Studies; Qualitative and Mixed Methods Research; Data Analysis Types; Innovative Processes of Qualitative Data Analysis; Qualitative Research in Web Contexts; and Qualitative Analysis with the Support of Specific Software. Given its breadth of coverage, the book offers a valuable resource for academics, researchers, teachers and students seeking information on the above topics, and on the use of Computer Assisted Qualitative Data Analysis (CAQDAS).

Research on general video game playing aims at designing agents or content generators that can perform well in multiple video games, possibly without knowing the game in advance and with little to no specific domain knowledge. The general video game AI framework and competition propose a challenge in which researchers can test their favorite AI methods with a potentially infinite number of games created using the Video Game Description Language. The open-source framework has been used since 2014 for running a challenge. Competitors around the globe submit their best approaches that aim to generalize well across games. Additionally, the framework has been used in AI modules by many higher-education institutions as assignments, or as proposed projects for final year (undergraduate and Master's) students and Ph.D. candidates. The present book, written by the developers and organizers of the framework, presents the most interesting highlights of the research performed by the authors duringthese years in this domain. It showcases work on methods to play the games, generators of content, and video game optimization. It also outlines potential further work in an area that offers multiple research directions for the future.

This book presents a contemporary view of the role of information quality in information fusion and decision making, and provides a formal foundation and the implementation strategies required for dealing with insufficient information quality in building fusion systems for decision making. Information fusion is the process of gathering, processing, and combining large amounts of information from multiple and diverse sources, including physical sensors to human intelligence reports and social media. That data and information may be unreliable, of low fidelity, insufficient resolution, contradictory, fake and/or redundant. Sources may provide unverified reports obtained from other sources resulting in correlations and biases. The success of the fusion processing depends on how well knowledge produced by the processing chain represents reality, which in turn depends on how adequate data are, how good and adequate are the models used, and how accurate, appropriate or applicable prior and contextual knowledge is. By offering contributions by leading experts, this book provides an unparalleled understanding of the problem of information quality in information fusion and decision-making for researchers and professionals in the field.

This book provides a broad yet detailed introduction to neural networks and machine learning in a statistical framework. A single, comprehensive resource for study and further research, it explores the major popular neural network models and statistical learning approaches with examples and exercises and allows readers to gain a practical working understanding of the content. This updated new edition presents recently published results and includes six new chapters that correspond to the recent advances in computational learning theory, sparse coding, deep learning, big data and cloud computing.Each chapter features state-of-the-art descriptions and significant research findings. The topics covered include:• multilayer perceptron;• the Hopfield network;• associative memory models;• clustering models and algorithms;• t he radial basis function network;• recurrent neural networks;• nonnegative matrix factorization;• independent component analysis;•probabilistic and Bayesian networks; and• fuzzy sets and logic.Focusing on the prominent accomplishments and their practical aspects, this book provides academic and technical staff, as well as graduate students and researchers with a solid foundation and comprehensive reference on the fields of neural networks, pattern recognition, signal processing, and machine learning.

This book discusses the principle of automotive intelligent technology from the point of view of modern sensing and intelligent control. Based on the latest research in the field, it explores safe driving with intelligent vision; intelligent monitoring of dangerous driving; intelligent detection of automobile power and transmission systems; intelligent vehicle navigation and transportation systems; and vehicle-assisted intelligent technology. It draws on the author's research in the field of automotive intelligent technology to explain the fundamentals of vehicle intelligent technology, from the information sensing principle to mathematical models and the algorithm basis, enabling readers to grasp the concepts of automotive intelligent technology. Opening up new scientific horizons and fostering innovative thinking, the book is a valuable resource for researchers as well as undergraduate and graduate students.

This student-friendly textbook encourages the development of programming skills through active practice by focusing on exercises that support hands-on learning. The Python Workbook provides a compendium of 186 exercises, spanning a variety of academic disciplines and everyday situations. Solutions to selected exercises are also provided, supported by brief annotations that explain the technique used to solve the problem, or highlight a specific point of Python syntax.This enhanced new edition has been thoroughly updated and expanded with additional exercises, along with concise introductions that outline the core concepts needed to solve them. The exercises and solutions require no prior background knowledge, beyond the material covered in a typical introductory Python programming course.Features: uses an accessible writing style and easy-to-follow structure; includes a mixture of classic exercises from the fields of computer science and mathematics, along with exercises that connect to other academic disciplines; presents the solutions to approximately half of the exercises; provides annotations alongside the solutions, which explain the approach taken to solve the problem and relevant aspects of Python syntax; offers a variety of exercises of different lengths and difficulties; contains exercises that encourage the development of programming skills using if statements, loops, basic functions, lists, dictionaries, files, and recursive functions.Undergraduate students enrolled in their first programming course and wishing to enhance their programming abilities will find the exercises and solutions provided in this book to be ideal for their needs.

This book introduces readers to robotics, industrial robot mechanisms, and types of robots, e.g. parallel robots, mobile robots and humanoid robots. The book is based on over 20 years of teaching robotics and has been extensively class tested and praised for its simplicity.It addresses the following subjects: a general introduction to robotics; basic characteristics of industrial robot mechanisms; position and movement of an object, which are described by homogenous transformation matrices; a geometric model of robot mechanisms expanded with robot wrist orientation description in this new edition; a brief introduction to the kinematics and dynamics of robots; robot sensors and planning of robot trajectories; fundamentals of robot vision; basic control schemes resulting in either desired end-effector trajectory or force; robot workcells with feeding devices and robot grippers.This second edition has been expanded to include the following new topics: parallel robots;collaborative robots; teaching of robots; mobile robots; and humanoid robots. The book is optimally suited for courses in robotics or industrial robotics and requires a minimal grasp of physics and mathematics.The 1st edition of this book won the Outstanding Academic Title distinction from the library magazine CHOICE in 2011.

This provides a comprehensive overview of the key principles of security concerns surrounding the upcoming Internet of Things (IoT), and introduces readers to the protocols adopted in the IoT. It also analyses the vulnerabilities, attacks and defense mechanisms, highlighting the security issues in the context of big data. Lastly, trust management approaches and ubiquitous learning applications are examined in detail. As such, the book sets the stage for developing and securing IoT applications both today and in the future.

This book presents the current trends, technologies, and challenges in Big Data in the diversified field of engineering and sciences. It covers the applications of Big Data ranging from conventional fields of mechanical engineering, civil engineering to electronics, electrical, and computer science to areas in pharmaceutical and biological sciences. This book consists of contributions from various authors from all sectors of academia and industries, demonstrating the imperative application of Big Data for the decision-making process in sectors where the volume, variety, and velocity of information keep increasing. The book is a useful reference for graduate students, researchers and scientists interested in exploring the potential of Big Data in the application of engineering areas.

This book presents state-of-the-art research advances in the field of biologically inspired cooperative control theories and their applications. It describes various biologically inspired cooperative control and optimization approaches and highlights real-world examples in complex industrial processes. Multidisciplinary in nature and closely integrating theory and practice, the book will be of interest to all university researchers, control engineers and graduate students in intelligent systems and control who wish to learn the core principles, methods, algorithms, and applications.

This book discusses digitalization trends and their concrete applications in business and societal contexts. It summarizes new findings from research, teaching and management activities comprising digital transformation, e-business, the representation of knowledge, human–computer interaction and business optimization. The trends discussed include artificial intelligence, virtual reality, robotics, blockchain, and many more. Professors and researchers who conduct research and teach at the interface between academia and business present the latest advances in their field. The book adopts the philosophy of applied sciences and combines both rigorous research and practical applications. As such, it addresses the needs of both professors and researchers, who are constantly seeking inspiration, and of managers seeking to tap the potential of the latest trends to take their business to the next level. Readers will find answers to pressing questions that arise in their daily work.

This book presents an authoritative collection of contributions reporting on fuzzy logic and decision theory, together with applications and case studies in economics and management science. Dedicated to Professor Jaume Gil Aluja in recognition of his pioneering work, the book reports on theories, methods and new challenges, thus offering not only a timely reference guide but also a source of new ideas and inspirations for graduate students and researchers alike.

This book presents a proposal for a new soft computing innovative method called by “CFE” forevaluation of the football matches of FIFA(IFAB) and UEFA to compute the true ‘Winner'. It is a research work in the area of ‘Football Science', being proposed to FIFA (IFAB) and UEFA, Zurich, Switzerland for consideration to replace the existing obsolete and weak rules of football matches of 90 minutes to declare the final ‘Winner'. In CFE, the final decision about any football match of 90 minutes is obtained “by computation”, by execution of a software called by ‘CFE-software'with the real time input values directly from the field on a number of highly significant parameters, some of them being continuous variables. The result of m-n goals at the end of 90 minutes play in a football match is just one of the many parameters for the computation of the ‘Winner'in our proposed CFE method. The evaluation is mainly based upon the application of Fuzzy Logic, ‘Fuzzy Pocket Machine', fast ComputerServer, good Communication system from playing-field to the server (as used in Cricket matches) and the CFE-software at the server. The Referees need not be experts in fuzzy set theory; they can be easily trained within just 30 minutes of demonstration on : how to use the ‘fuzzy pocket machine'for giving real time inputs to the database at the server.

Distributed robotics is an interdisciplinary and rapidly growing area, combining research in computer science, communication and control systems, and electrical and mechanical engineering. Distributed robotic systems can autonomously solve complex problems while operating in highly unstructured real-world environments. They are expected to play a major role in addressing future societal needs, for example, by improving environmental impact assessment, food supply, transportation, manufacturing, security, and emergency and rescue services. The goal of the International Symposium on Distributed Autonomous Robotic Systems (DARS) is to provide a forum for scientific advances in the theory and practice of distributed autonomous robotic systems. This volume of proceedings include 47 original contributions presented at the 13th International Symposium on Distributed Autonomous Robotic Systems (DARS 2016), which was held at the Natural History Museum in London, UK, from November 7thto 9th, 2016. The selected papers in this volume are authored by leading researchers from around the world, thereby providing a broad coverage and perspective of the state-of-the-art technologies, algorithms, system architectures, and applications in distributed robotic systems. The book is organized into seven parts, representative of critical long-term and emerging research thrusts in the multi-robot community: Distributed Coverage and Exploration; Multi-Robot Control; Multi-Robot Estimation; Multi-Robot Planning; Modular Robots and Smart Materials; Swarm Robotics; and Multi-Robot Systems in Applications.

In this book, a methodology for parameter adaptation in meta-heuristic op-timization methods is proposed. This methodology is based on using met-rics about the population of the meta-heuristic methods, to decide through a fuzzy inference system the best parameter values that were carefully se-lected to be adjusted. With this modification of parameters we want to find a better model of the behavior of the optimization method, because with the modification of parameters, these will affect directly the way in which the global or local search are performed.Three different optimization methods were used to verify the improve-ment of the proposed methodology. In this case the optimization methods are: PSO (Particle Swarm Optimization), ACO (Ant Colony Optimization) and GSA (Gravitational Search Algorithm), where some parameters are se-lected to be dynamically adjusted, and these parameters have the most im-pact in the behavior of each optimization method.Simulation results show that the proposed methodology helps to each optimization method in obtaining better results than the results obtained by the original method without parameter adjustment.

This unique book presents innovative and state-of-the-art computational models for determining the optimal truck–loader selection and allocation strategy for use in large and complex mining operations. The authors provide comprehensive information on the methodology that has been developed over the past 50 years, from the early ad hoc spreadsheet approaches to today's highly sophisticated and accurate mathematical-based computational models. The authors'approach is motivated and illustrated by real case studies provided by our industry collaborators. The book is intended for a broad audience, ranging from mathematicians with an interest in industrial applications to mining engineers who wish to utilize the most accurate, efficient, versatile and robust computational models in order to refine their equipment selection and allocation strategy. As materials handling costs represent a significant component of total costs for mining operations, applyingthe optimization methodology developed here can substantially improve their competitiveness

This three-volume set of books presents advances in the development of concepts and techniques in the area of new technologies and contemporary information system architectures. It guides readers through solving specific research and analytical problems to obtain useful knowledge and business value from the data. Each chapter provides an analysis of a specific technical problem, followed by the numerical analysis, simulation and implementation of the solution to the problem. The books constitute the refereed proceedings of the 2017 38th International Conference “Information Systems Architecture and Technology,” or ISAT 2017, held on September 17–19, 2017 in Szklarska Poręba, Poland. The conference was organized by the Computer Science and Management Systems Departments, Faculty of Computer Science and Management, Wroclaw University of Technology, Poland. The papers have been organized into topical parts: Part I— includes discourseson topics including, but not limited to, Artificial Intelligence Methods, Knowledge Discovery and Data Mining, Big Data, Knowledge Discovery and Data Mining, Knowledge Based Management, Internet of Things, Cloud Computing and High Performance Computing, Distributed Computer Systems, Content Delivery Networks, and Service Oriented Computing. Part II—addresses topics including, but not limited to, System Modelling for Control, Recognition and Decision Support, Mathematical Modelling in Computer System Design, Service Oriented Systems and Cloud Computing and Complex Process Modeling. Part III—deals with topics including, but not limited to, Modeling of Manufacturing Processes, Modeling an Investment Decision Process, Management of Innovation, Management of Organization.

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

This book presents the refereed proceedings of the third International Conference on Advanced Machine Learning Technologies and Applications, AMLTA 2018, held in Cairo, Egypt, on February 22–24, 2018, and organized by the Scientific Research Group in Egypt (SRGE). The papers cover current research in machine learning, big data, Internet of Things, biomedical engineering, fuzzy logic, security, and intelligence swarms and optimization.

This volume includes papers presented at SOCO 2017, CISIS 2017, and ICEUTE 2017, all conferences held in the beautiful and historic city of León (Spain) in September 2017.Soft computing represents a collection of computational techniques in machine learning, computer science, and some engineering disciplines, which investigate, simulate, and analyze highly complex issues and phenomena.These proceedings feature 48 papers from the 12th SOCO 2017, covering topics such as artificial intelligence and machine learning applied to health sciences; and soft computing methods in manufacturing and management systems.The book also presents 18 papers from the 10th CISIS 2017, which provided a platform for researchers from the fields of computational intelligence, information security, and data mining to meet and discuss the need for intelligent, flexible behavior by large, complex systems, especially in mission-critical domains. It addresses various topics, like identification, simulation and prevention of security and privacy threats in modern communication networks Furthermore, the book includes 8 papers from the 8th ICEUTE 2017. The selection of papers for all three conferences was extremely rigorous in order to maintain the high quality and we would like to thank the members of the Program Committees for their hard work in the reviewing process.

This is the first volume of proceedings including selected papers from the International Conference on IT Convergence and Security (ICITCS) 2017, presenting a snapshot of the latest issues encountered in this field. It explores how IT convergence and security issues are core to most current research, and industrial and commercial activities. It consists of contributions covering topics such as machine learning & deep learning, communication and signal processing, computer vision and applications, future network technology, artificial intelligence and robotics. ICITCS 2017 is the latest in a series of highly successful International Conferences on IT Convergence and Security, previously held in Prague, Czech Republic(2016), Kuala Lumpur, Malaysia (2015) Beijing, China (2014), Macau, China (2013), Pyeong Chang, Korea (2012), and Suwon, Korea (2011).

Jeder kennt sie. Smartphones, die mit uns sprechen, Armbanduhren, die unsere Gesundheitsdaten aufzeichnen, Arbeitsabläufe, die sich automatisch organisieren, Autos, Flugzeuge und Drohnen, die sich selber steuern, Verkehrs- und Energiesysteme mit autonomer Logistik oder Roboter, die ferne Planeten erkunden, sind technische Beispiele einer vernetzten Welt intelligenter Systeme. Machine Learning verändert unsere Zivilisation dramatisch. Wir verlassen uns immer mehr auf effiziente Algorithmen, weil die Komplexität unserer zivilisatorischen Infrastruktur sonst nicht zu bewältigen ist. Aber wie sicher sind KI-Algorithmen? Diese Herausforderung wird in der 2.Auflage aufgegriffen: Komplexe neuronale Netze werden mit riesigen Datenmengen (Big Data) gefüttert und trainiert. Die Anzahl der dazu notwenigen Parameter explodiert exponentiell. Niemand weiß genau, was sich in diesen „Black Boxes“ im Einzelnen abspielt. Im Machine Learning benötigen wir mehr Erklärung (explainability) und Zurechnung (accountability) von Ursachen und Wirkungen, um ethische und rechtliche Fragen der Verantwortung (z.B. beim autonomen Fahren oder in der Medizin) entscheiden zu können! Seit ihrer Entstehung ist die KI-Forschung mit großen Visionen über die Zukunft der Menschheit verbunden. Sie ist bereits eine Schlüsseltechnologie, die den globalen Wettstreit der Gesellschaftssysteme entscheiden wird. „Künstliche Intelligenz und Verantwortung“ ist eine weitere zentrale Ergänzung der 2. Auflage: Wie sollen wir unsere individuellen Freiheitsrechte in der KI-Welt sichern? Dieses Buch ist ein Plädoyer für Technikgestaltung: KI muss sich als Dienstleistung in der Gesellschaft bewähren.

Prepare yourselves for the coming Cyber Revolution! Over time, humankind has transformed from hunter-gatherer to farmer, from farmer to industrial worker, and from industrial worker to service provider. Now, we are on the cusp of a fourth transformative wave, spurred by climate change, exponential population growth, and our ever-increasing reliance on technology.This Copernicus book follows the stream of changes we will likely experience over the next few decades. These will involve the design and planning of smart cities and vital new mega-cities, as well as the use of sophisticated artificial intelligence and knowledge systems in our professional and everyday lives. The book shows how the nature of work, economics, taxation, social intercourse, and a slew of other global human endeavors will almost certainly undergo fundamental shifts during this time.Despite the many crises the world is gearing up to face, this book is not all doom and gloom – it is a call to action, a guide to how we might harness novel technologies in space and cyberspace to address our most urgent needs.

This book contains some selected papers from the International Conference on Extreme Learning Machine 2016, which was held in Singapore, December13-15, 2016. This conference will provide a forum for academics, researchers and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the ELM technique and brain learning. Extreme Learning Machines (ELM) aims to break the barriers between the conventional artificial learning techniques and biological learning mechanism. ELM represents a suite of (machine or possibly biological) learning techniques in which hidden neurons need not be tuned. ELM learning theories show that very effective learning algorithms can be derived based on randomly generated hidden neurons (with almost any nonlinear piecewise activation functions), independent of training data and application environments. Increasingly, evidence from neurosciencesuggests that similar principles apply in biological learning systems. ELM theories and algorithms argue that “random hidden neurons” capture an essential aspect of biological learning mechanisms as well as the intuitive sense that the efficiency of biological learning need not rely on computing power of neurons. ELM theories thus hint at possible reasons why the brain is more intelligent and effective than current computers. ELM offers significant advantages over conventional neural network learning algorithms such as fast learning speed, ease of implementation, and minimal need for human intervention. ELM also shows potential as a viable alternative technique for large‐scale computing and artificial intelligence. This book covers theories, algorithms ad applications of ELM. It gives readers a glance of the most recent advances of ELM.

This proceedings book gathers contributions presented at the 2nd International Conference of Mechatronics and Cyber-MixMechatronics/ICOMECYME, organized by the National Institute of R&D in Mechatronics and Measurement Technique in Bucharest, Romania, on September 6th–7th, 2018. Further, it reflect the expansion of the field of Mechatronics, which has yielded newer trans-disciplinary fields including Adaptronics, Integronics, and Cyber-Mix-Mechatronics. These are also the topics addressed by the respective book chapters. The conference has a rich scientific tradition and attracts specialists from all over the world – including North America, South America, and Asia. ICOMECYME is focused on presenting research results and is mainly directed at academics and advanced students, but also offers a venue for interacting with R&D experts. These proceedings will especially benefit entrepreneurs who want to invest in research and who are open for collaborations.

This book offers a comprehensive overview of ensemble learning in the field of feature selection (FS), which consists of combining the output of multiple methods to obtain better results than any single method. It reviews various techniques for combining partial results, measuring diversity and evaluating ensemble performance. With the advent of Big Data, feature selection (FS) has become more necessary than ever to achieve dimensionality reduction. With so many methods available, it is difficult to choose the most appropriate one for a given setting, thus making the ensemble paradigm an interesting alternative. The authors first focus on the foundations of ensemble learning and classical approaches, before diving into the specific aspects of ensembles for FS, such as combining partial results, measuring diversity and evaluating ensemble performance. Lastly, the book shows examples of successful applications of ensembles for FS and introduces the new challenges thatresearchers now face. As such, the book offers a valuable guide for all practitioners, researchers and graduate students in the areas of machine learning and data mining.

This book collects recent theoretical advances and concrete applications of learning automata (LAs) in various areas of computer science, presenting a broad treatment of the computer science field in a survey style. Learning automata (LAs) have proven to be effective decision-making agents, especially within unknown stochastic environments. The book starts with a brief explanation of LAs and their baseline variations. It subsequently introduces readers to a number of recently developed, complex structures used to supplement LAs, and describes their steady-state behaviors. These complex structures have been developed because, by design, LAs are simple units used to perform simple tasks; their full potential can only be tapped when several interconnected LAs cooperate to produce a group synergy.In turn, the next part of the book highlights a range of LA-based applications in diverse computer science domains, from wireless sensor networks, to peer-to-peer networks, to complex social networks, and finally to Petri nets. The book accompanies the reader on a comprehensive journey, starting from basic concepts, continuing to recent theoretical findings, and ending in the applications of LAs in problems from numerous research domains. As such, the book offers a valuable resource for all computer engineers, scientists, and students, especially those whose work involves the reinforcement learning and artificial intelligence domains.

This book is the fourth volume of the sub series of the Lecture Notes in Mobility dedicated to Road Vehicle Automation. lts chapters have been written by researchers, engineers and analysts from all around the globe. Topics covered include public sector activities, human factors and challenges, ethical, legal, energy and technology perspectives, vehicle systems development, as well as transportation infrastructure and planning. The book is based on the Automated Vehicles Symposium which took place in San Francisco, California (USA) in July 2016.

Experimental Robotics XV is the collection of papers presented at the International Symposium on Experimental Robotics, Roppongi, Tokyo, Japan on October 3-6, 2016. 73 scientific papers were selected and presented after peer review. The papers span a broad range of sub-fields in robotics including aerial robots, mobile robots, actuation, grasping, manipulation, planning and control and human-robot interaction, but shared cutting-edge approaches and paradigms to experimental robotics. The readers will find a breadth of new directions of experimental robotics. The International Symposium on Experimental Robotics is a series of bi-annual symposia sponsored by the International Foundation of Robotics Research, whose goal is to provide a forum dedicated to experimental robotics research. Robotics has been widening its scientific scope, deepening its methodologies and expanding its applications. However, the significance of experiments remains and will remain atthe center of the discipline. The ISER gatherings are a venue where scientists can gather and talk about robotics based on this central tenet.

This book presents extended versions of papers originally presented and discussed at the 3rd International Doctoral Symposium on Applied Computation and Security Systems (ACSS 2016) held from August 12 to 14, 2016 in Kolkata, India. The symposium was jointly organized by the AGH University of Science & Technology, Cracow, Poland; Ca'Foscari University, Venice, Italy; and the University of Calcutta, India. The book is divided into two volumes, Volumes 3 and 4, and presents dissertation works in the areas of Image Processing, Biometrics-based Authentication, Soft Computing, Data Mining, Next-Generation Networking and Network Security, Remote Healthcare, Communications, Embedded Systems, Software Engineering and Service Engineering. The first two volumes of the book published the works presented at the ACSS 2015, which was held from May 23 to 25, 2015 in Kolkata, India.

This book highlights the latest achievements concerning the theory, methods and practice of fault diagnostics, fault tolerant systems and cyber safety. When considering the diagnostics of industrial processes and systems, increasingly important safety issues cannot be ignored. In this context, diagnostics plays a crucial role as a primary measure of the improvement of the overall system safety integrity level. Obtaining the desired diagnostic coverage or providing an appropriate level of inviolability of the integrity of a system is now practically inconceivable without the use of fault detection and isolation methods.Given the breadth and depth of its coverage, the book will be of interest to researchers faced with the challenge of designing technical and medical diagnosis systems, as well as junior researchers and students in the fields of automatic control, robotics, computer science and artificial intelligence.

This book presents compact and informative descriptions of the most promising new projects in brain-computer interface (BCI) research. As in earlier volumes in this series, the contributions come from many of the best-known groups in BCI research. Each of these chapters provides an overview of a project that was nominated for the most prestigious award in the BCI community: the Annual BCI Research Award. The book also contains an introduction and discussion with a review of major trends reflected in the awards. This volume also introduces a new type of contribution, namely a chapter'Trends in BCI Research'that summarizes a top trend in the BCI research community. This year's'Trends in BCI Research'addresses BCI technology to help patients with disorders of consciousness (DOC) and related conditions, including new work that goes beyond communication to diagnosis and even prediction.

This book is devoted to Multiobjective Optimization Design (MOOD) procedures for controller tuning applications, by means of Evolutionary Multiobjective Optimization (EMO). It presents developments in tools, procedures and guidelines to facilitate this process, covering the three fundamental steps in the procedure: problem definition, optimization and decision-making. The book is divided into four parts. The first part, Fundamentals, focuses on the necessary theoretical background and provides specific tools for practitioners. The second part, Basics, examines a range of basic examples regarding the MOOD procedure for controller tuning, while the third part, Benchmarking, demonstrates how the MOOD procedure can be employed in several control engineering problems. The fourth part, Applications, is dedicated to implementing the MOOD procedure for controller tuning in real processes.

This book offers a broad, cohesive overview of the field of data privacy. It discusses, from a technological perspective, the problems and solutions of the three main communities working on data privacy: statistical disclosure control (those with a statistical background), privacy-preserving data mining (those working with data bases and data mining), and privacy-enhancing technologies (those involved in communications and security) communities.Presenting different approaches, the book describes alternative privacy models and disclosure risk measures as well as data protection procedures for respondent, holder and user privacy. It also discusses specific data privacy problems and solutions for readers who need to deal with big data.

This handbook provides insights into becoming a better and more evolved athlete. It offers aspiring athletes, regardless of skill level, a better understanding of their bodies and how to unlock the unlimited potential of muscles without injury. It focuses on the “superhero” muscle: the iliopsoas, and also sheds light on Diamond-Corporation's new technology and elite athleticism, and how these can contribute to a healthier life. Lastly, the authors explore the mindset of success and provide exercises for remaining calm under pressure. This stand-alone book is the sequel to Paradigm Shift for Future Tennis and Enhancing Performance and Reducing Stress in Sport (2014, Springer).This book is written by scientists, whose expertise collectively spans the fields of biomechanics, clinical surgery, current and former elite athleticism, engineering and naturopath doctoral work. Together, they aim to inspire and educate athletes on how to improve their sports performance by using new technologies, world class biomechanics knowledge and ancient herbal medicines.

This book provides an introduction to fuzzy logic approaches useful in image processing. The authors start by introducing image processing tasks of low and medium level such as thresholding, enhancement, edge detection, morphological filters, and segmentation and shows how fuzzy logic approaches apply. The book is divided into two parts. The first includes vagueness and ambiguity in digital images, fuzzy image processing, fuzzy rule based systems, and fuzzy clustering. The second part includes applications to image processing, image thresholding, color contrast enhancement, edge detection, morphological analysis, and image segmentation. Throughout, they describe image processing algorithms based on fuzzy logic under methodological aspects in addition to applicative aspects. Implementations in java are provided for the various applications.

Das Buch führt anschaulich und verständlich in das Gebiet der intelligenten Verfahren ein. In geschlossenen Darstellungen zeigt es zuerst die theoretischen Grundlagen und anschließend praktische Beispiele, wobei bei den Beispielen auch fehlerhafte Ansätze gezeigt werden.Ausgehend von linearen Systemen und ihren Einschränkungen werden nichtlineare Systeme sowie grundlegende Lernverfahren eingeführt. Darauf aufbauend werden intelligente Verfahren, z.B. der lernfähige, nichtlineare Beobachter, entwickelt sowie die Identifikation von nichtlinearen Systemen und deren Optimierung behandelt. Anschließend werden Regelungsverfahren von nichtlinearen Systemen vorgestellt, wobei die modellbasierte adaptive Regelung sowie die Regelung von unbekannten Systemen Schwerpunkte sind. Den Abschluss bildet ein Kapitel über Fuzzy-Logik.Die Verfahren können bei vielen nichtlinearen Systemen angewendet werden und wurden bereits äußerst erfolgreich in der Medizin, in der Robotik und in der Getriebesteuerung von Hybridfahrzeugen eingesetzt.Neu an der zweiten Auflage sind Kapitel über robuste Schätzverfahren und Concurrent Learning.Die ZielgruppenDas Werk richtet sich an Studierende und Wissenschaftler der Ingenieurwissenschaften, Informatik und Mathematik sowie Ingenieure in der Praxis.

This book presents the proceedings of the 19th International Conference on Interactive Collaborative Learning, held 21-23 September 2016 at Clayton Hotel in Belfast, UK. We are currently witnessing a significant transformation in the development of education. The impact of globalisation on all areas of human life, the exponential acceleration of developments in both technology and the global markets, and the growing need for flexibility and agility are essential and challenging elements of this process that have to be addressed in general, but especially in the context of engineering education. To face these topical and very real challenges, higher education is called upon to find innovative responses. Since being founded in 1998, this conference has consistently been devoted to finding new approaches to learning, with a focus on collaborative learning. Today the ICL conferences have established themselves as a vital forum for the exchange of information on key trends and findings, and of practical lessons learned while developing and testing elements of new technologies and pedagogies in learning.

With this brief, the authors present algorithms for model-free stabilization of unstable dynamic systems. An extremum-seeking algorithm assigns the role of a cost function to the dynamic system's control Lyapunov function (clf) aiming at its minimization. The minimization of the clf drives the clf to zero and achieves asymptotic stabilization. This approach does not rely on, or require knowledge of, the system model. Instead, it employs periodic perturbation signals, along with the clf. The same effect is achieved as by using clf-based feedback laws that profit from modeling knowledge, but in a time-average sense. Rather than use integrals of the systems vector field, we employ Lie-bracket-based (i.e., derivative-based) averaging. The brief contains numerous examples and applications, including examples with unknown control directions and experiments with charged particle accelerators. It is intended for theoretical control engineers and mathematicians, and practitioners working in various industrial areas and in robotics.

Evolving agents to play games is a promising technology. It can provide entertaining opponents for games like Chess or Checkers, matched to a human opponent as an alternative to the perfect and unbeatable opponents embodied by current artifical intelligences. Evolved agents also permit us to explore the strategy space of mathematical games like Prisoner's Dilemma and Rock-Paper-Scissors. This book summarizes, explores, and extends recent work showing that there are many unsuspected factors that must be controlled in order to create a plausible or useful set of agents for modeling cooperation and conflict, deal making, or other social behaviors. The book also provides a proposal for an agent training protocol that is intended as a step toward being able to train humaniform agents—in other words, agents that plausibly model human behavior.

This book presents the latest research in hybrid intelligent systems. It includes 57 carefully selected papers from the 16th International Conference on Hybrid Intelligent Systems (HIS 2016) and the 8th World Congress on Nature and Biologically Inspired Computing (NaBIC 2016), held on November 21–23, 2016 in Marrakech, Morocco. HIS - NaBIC 2016 was jointly organized by the Machine Intelligence Research Labs (MIR Labs), USA; Hassan 1st University, Settat, Morocco and University of Sfax, Tunisia. Hybridization of intelligent systems is a promising research field in modern artificial/computational intelligence and is concerned with the development of the next generation of intelligent systems. The conference's main aim is to inspire further exploration of the intriguing potential of hybrid intelligent systems and bio-inspired computing. As such, the book is a valuable resource for practicing engineers /scientists and researchers working in the field of computational intelligence and artificial intelligence.

This book gathers the proceedings of the 2nd International Conference on Advanced Intelligent Systems and Informatics (AISI2016), which took place in Cairo, Egypt during October 24–26, 2016. This international interdisciplinary conference, which highlighted essential research and developments in the field of informatics and intelligent systems, was organized by the Scientific Research Group in Egypt (SRGE) and sponsored by the IEEE Computational Intelligence Society (Egypt chapter) and the IEEE Robotics and Automation Society (Egypt Chapter). The book's content is divided into four main sections: Intelligent Language Processing, Intelligent Systems, Intelligent Robotics Systems, and Informatics.

This volume encompasses state-of-the-art developments in AI-based reactive scheduling for real-time operation management in manufacturing shop floors. It is a collection of papers from the Second International Workshop of the IFIP Working Group 5.7 which brought together researchers from management information systems and knowledge engineering to expand the focus on applying new knowledge-based techniques.