This book explores the ways in which the broad range of technologies that make up the smart city infrastructure can be harnessed to incorporate more playfulness into the day-to-day activities that take place within smart cities, making them not only more efficient but also more enjoyable for the people who live and work within their confines. The book addresses various topics that will be of interest to playable cities stakeholders, including the human-computer interaction and game designer communities, computer scientists researching sensor and actuator technology in public spaces, urban designers, and (hopefully) urban policymakers. This is a follow-up to another book on Playable Cities edited by Anton Nijholt and published in 2017 in the same book series, Gaming Media and Social Effects.

This scholarly treasury of over 450 distinguished quotations, divided into 170 categories, focuses on the best thinking in the disciplines of psychology, philosophy, and artificial intelligence, from the classical period of Greece to contemporary cognitive science. Quotations are arranged chronologically within categories. This work will be of interest to scholars and professionals in psychology, artificial intelligence, and cognitive science as well as undergraduate and graduate students in these disciplines.

This book offers a comprehensive reference guide to intelligence systems in environmental management. It provides readers with all the necessary tools for solving complex environmental problems, where classical techniques cannot be applied. The respective chapters, written by prominent researchers, explain a wealth of both basic and advanced concepts including ant colony, genetic algorithms, evolutionary algorithms, fuzzy multi-criteria decision making tools, particle swarm optimization, agent-based modelling, artificial neural networks, simulated annealing, Tabu search, fuzzy multi-objective optimization, fuzzy rules, support vector machines, fuzzy cognitive maps, cumulative belief degrees, and many others. To foster a better understanding, all the chapters include relevant numerical examples or case studies. Taken together, they form an excellent reference guide for researchers, lecturers and postgraduate students pursuing research on complex environmental problems. Moreover, by extending all the main aspects of classical environmental solution techniques to its intelligent counterpart, the book presents a dynamic snapshot on the field that is expected to stimulate new directions and stimulate new ideas and developments.

This book presents state-of-the-art computational attention models that have been successfully tested in diverse application areas and can build the foundation for artificial systems to efficiently explore, analyze, and understand natural scenes. It gives a comprehensive overview of the most recent computational attention models for processing visual and acoustic input. It covers the biological background of visual and auditory attention, as well as bottom-up and top-down attentional mechanisms and discusses various applications. In the first part new approaches for bottom-up visual and acoustic saliency models are presented and applied to the task of audio-visual scene exploration of a robot. In the second part the influence of top-down cues for attention modeling is investigated.

This book presents a cutting-edge research procedure in the Nature-Inspired Computing (NIC) domain and its connections with computational intelligence areas in real-world engineering applications. It introduces readers to a broad range of algorithms, such as genetic algorithms, particle swarm optimization, the firefly algorithm, flower pollination algorithm, collision-based optimization algorithm, bat algorithm, ant colony optimization, and multi-agent systems. In turn, it provides an overview of meta-heuristic algorithms, comparing the advantages and disadvantages of each. Moreover, the book provides a brief outline of the integration of nature-inspired computing techniques and various computational intelligence paradigms, and highlights nature-inspired computing techniques in a range of applications, including: evolutionary robotics, sports training planning, assessment of water distribution systems, flood simulation and forecasting, traffic control, gene expression analysis, antenna array design, and scheduling/dynamic resource management.

This book describes load modeling approaches for complex work pieces and batch forgings, and demonstrates analytical modeling and data-driven modeling approaches for known and unknown complex forging processes. It overcomes the current shortcomings of modeling, analysis and control approaches, presenting contributions in three major areas: In the first, several novel modeling approaches are proposed: a process/shape-decomposition modeling method to help estimate the deformation force; an online probabilistic learning machine for the modeling of batch forging processes; and several data-driven identification and modeling approaches for unknown forging processes under different work conditions. The second area develops model-based dynamic analysis methods to derive the conditions of stability and creep. Lastly, several novel intelligent control methods are proposed for complex forging processes. One of the most serious problems in forging forming involves the inaccurate forging conditions, velocity and position offered by the hydraulic actuator due to the complexity of both the deformation process of the metal work piece and the motion process of the hydraulic actuator. The book summarizes the current weaknesses of modeling, analysis and control approaches. are summarized as follows: a) With the current modeling approaches it is difficult to model complex forging processes with unknown parameters, as they only model the dynamics in local working areas but do not effectively model unknown nonlinear systems across multiple working areas; further, they do not take the batch forging process into account, let alone its distribution modeling. b) All previous dynamic analysis studies simplify the forging system to having a single-frequency pressure fluctuation and neglect the influences of non-linear load force. Further, they fail to take the flow equation in both valves and cylinders into account. c) Conventional control approaches only consider the linear deformation force and pay no attention to sudden changes and the motion synchronization for the multi-cylinder system, making them less effective for complex, nonlinear time-varying forging processes subject to sudden changes.

This book proposes several commonly used interval-valued solution concepts of interval-valued cooperative games with transferable utility. It thoroughly investigates these solutions, thereby establishing the properties, models, methods, and applications. The first chapter proposes the interval-valued least square solutions and quadratic programming models, methods, and properties. Next, the satisfactory-degree-based non-linear programming models for computing interval-valued cores and corresponding bisection algorithm are explained. Finally, the book explores several simplification methods of interval-valued solutions: the interval-valued equal division and equal surplus division values; the interval-valued Shapley, egalitarian Shapley, and discounted Shapley values; the interval-valued solidarity and generalized solidarity values; and the interval-valued Banzhaf value. This book is designed for individuals from different fields and disciplines, such as decision science, game theory, management science, operations research, fuzzy sets or fuzzy mathematics, applied mathematics, industrial engineering, finance, applied economics, expert system, and social economy as well as artificial intelligence. Moreover, it is suitable for teachers, postgraduates, and researchers from different disciplines: decision analysis, management, operations research, fuzzy mathematics, fuzzy system analysis, applied mathematics, systems engineering, project management, supply chain management, industrial engineering, applied economics, and hydrology and water resources.

This PALO volume constitutes the Proceedings of the 19th Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES 2015), held in Bangkok, Thailand, November 22-25, 2015. The IES series of conference is an annual event that was initiated back in 1997 in Canberra, Australia. IES aims to bring together researchers from countries of the Asian Pacific Rim, in the fields of intelligent systems and evolutionary computation, to exchange ideas, present recent results and discuss possible collaborations. Researchers beyond Asian Pacific Rim countries are also welcome and encouraged to participate. The theme for IES 2015 is "Transforming Big Data into Knowledge and Technological Breakthroughs". The host organization for IES 2015 is the School of Information Technology (SIT), King Mongkut's University of Technology Thonburi (KMUTT), and it is technically sponsored by the International Neural Network Society (INNS). IES 2015 is collocated with three other conferences; namely, The 6th International Conference on Computational Systems-Biology and Bioinformatics 2015 (CSBio 2015), The 7th International Conference on Advances in Information Technology 2015 (IAIT 2015) and The 10th International Conference on e-Business 2015 (iNCEB 2015), as a major part of series of events to celebrate the SIT 20th anniversary and the KMUTT 55th anniversary.

This volume presents the first part of the proceedings of the Mediterranean Conference on Information & Communication Technologies (MedICT 2015), which was held at Saidia, Morocco during 7-9 May, 2015. MedICT provides an excellent international forum to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development. The conference has also a special focus on enabling technologies for societal challenges, and seeks to address multidisciplinary challenges in Information & Communication Technologies such as health, demographic change, wellbeing, security and sustainability issues. The proceedings publish high quality papers which are closely related to the various theories, as well as emerging and practical applications of particular interest to the ICT community. This first volume provides a compact yet broad view of recent developments in devices, technologies and processing, and covers recent research areas in the field including Microwave Devices and Printed Antennas, Advances in Optical and RF Devices and Applications, Signal Processing and Information Theory, Wireless and Optical Technologies and Techniques, Computer Vision, Optimization and Modeling in Wireless Communication Systems, Modeling, Identification and Biomedical Signal Processing, Photovoltaic Cell & Systems, RF Devices and Antennas for Wireless Applications, RFID, Ad Hoc and Networks Issues.

This book gathers the peer-reviewed proceedings of the 12th Annual Meeting of the Bulgarian Section of the Society for Industrial and Applied Mathematics, BGSIAM'17, held in Sofia, Bulgaria, in December 2017. The general theme of BGSIAM'17 was industrial and applied mathematics, with a particular focus on: high-performance computing, numerical methods and algorithms, analysis of partial differential equations and their applications, mathematical biology, control and uncertain systems, stochastic models, molecular dynamics, neural networks, genetic algorithms, metaheuristics for optimization problems, generalized nets, and Big Data.

In an evaluation of the strengths and limitations of artificial intelligence in a number of intellectual domains, Wagman draws comparisons with human cognitive ability in those domains, and assesses its role as a theoretical model, as a collaborator, or as a competitor of the human mind. This book distinguishes itself in its structured and detailed account of advancing intellectual developments in the science of artificial intelligence as opposed to a highly technical or vague philosophical treatment of the topic.

This book provides a deep analysis and wide coverage of the very strong trend in computer vision and visual indexing and retrieval, covering such topics as incorporation of models of Human Visual attention into analysis and retrieval tasks. It makes the bridge between psycho-visual modelling of Human Visual System and the classical and most recent models in visual content indexing and retrieval. The large spectrum of visual tasks, such as recognition of textures in static images, of actions in video content, image retrieval, different methods of visualization of images and multimedia content based on visual saliency are presented by the authors. Furthermore, the interest in visual content is modelled with the means of the latest classification models such as Deep Neural Networks is also covered in this book. This book is an exceptional resource as a secondary text for researchers and advanced level students, who are involved in the very wide research in computer vision, visual information indexing and retrieval. Professionals working in this field will also be interested in this book as a reference.

This book presents recent research in the field of interaction between computational intelligence and mathematics, ranging from theory to applications. Computational intelligence, or soft computing consists of various bio-inspired methods, especially fuzzy systems, artificial neural networks, evolutionary and memetic algorithms. These research areas were initiated by professionals in various applied fields, such as engineers, economists, and financial and medical experts. Although computational intelligence offered solutions (at least quasi-optimal solutions) for problems with high complexity, vague and undeterministic features, initially little attention was paid to the mathematical models and analysis of the methods successfully applied. A typical example is the extremely successful Mamdani-algorithm, and its modifications and extensions, applied since the mid-1970s, where the first analysis of the simplest cases, showing why this algorithm was so efficient and stable, was not given until the early 1990s. Since the mid-2000s, the authors have organized international conferences annually to focus on the mathematical methodological issues in connection with computational intelligence approaches. These conferences have attracted a large number of submissions with a wide scope of topics and quality. The editors selected several high-quality papers and approached the authors to submit an essentially extended and improved book chapter based on the lectures.This volume is the first contributed book on the subject.

This book thoroughly investigates the underlying theoretical basis of membrane computing models, and reveals their latest applications. In addition, to date there have been no illustrative case studies or complex real-life applications that capitalize on the full potential of the sophisticated membrane systems computational apparatus; gaps that this book remedies. By studying various complex applications - including engineering optimization, power systems fault diagnosis, mobile robot controller design, and complex biological systems involving data modeling and process interactions - the book also extends the capabilities of membrane systems models with features such as formal verification techniques, evolutionary approaches, and fuzzy reasoning methods. As such, the book offers a comprehensive and up-to-date guide for all researchers, PhDs and undergraduate students in the fields of computer science, engineering and the bio-sciences who are interested in the applications of natural computing models.

This book is devoted to one of the most famous examples of automation handling tasks - the "bin-picking" problem. To pick up objects, scrambled in a box is an easy task for humans, but its automation is very complex. In this book three different approaches to solve the bin-picking problem are described, showing how modern sensors can be used for efficient bin-picking as well as how classic sensor concepts can be applied for novel bin-picking techniques. 3D point clouds are firstly used as basis, employing the known Random Sample Matching algorithm paired with a very efficient depth map based collision avoidance mechanism resulting in a very robust bin-picking approach. Reducing the complexity of the sensor data, all computations are then done on depth maps. This allows the use of 2D image analysis techniques to fulfill the tasks and results in real time data analysis. Combined with force/torque and acceleration sensors, a near time optimal bin-picking system emerges. Lastly, surface normal maps are employed as a basis for pose estimation. In contrast to known approaches, the normal maps are not used for 3D data computation but directly for the object localization problem, enabling the application of a new class of sensors for bin-picking.

This book explains advanced theoretical and application-related issues in grammatical inference, a research area inside the inductive inference paradigm for machine learning. The first three chapters of the book deal with issues regarding theoretical learning frameworks; the next four chapters focus on the main classes of formal languages according to Chomsky's hierarchy, in particular regular and context-free languages; and the final chapter addresses the processing of biosequences. The topics chosen are of foundational interest with relatively mature and established results, algorithms and conclusions. The book will be of value to researchers and graduate students in areas such as theoretical computer science, machine learning, computational linguistics, bioinformatics, and cognitive psychology who are engaged with the study of learning, especially of the structure underlying the concept to be learned. Some knowledge of mathematics and theoretical computer science, including formal language theory, automata theory, formal grammars, and algorithmics, is a prerequisite for reading this book.

The primary aim of this volume is to provide researchers and engineers from both academia and industry with up-to-date coverage of recent advances in the fields of robotic welding, intelligent systems and automation. It gathers selected papers from the 2018 International Conference on Robotic Welding, Intelligence and Automation (RWIA 2018), held Oct 20-22, 2018 in Guangzhou, China. The contributions reveal how intelligentized welding manufacturing (IWM) is becoming an inescapable trend, just as intelligentized robotic welding is becoming a key technology. The volume is divided into four main parts: Intelligent Techniques for Robotic Welding, Sensing in Arc Welding Processing, Modeling and Intelligent Control of Welding Processing, and Intelligent Control and its Applications in Engineering.

The collected works of Turing, including a substantial amount of unpublished material, will comprise four volumes: Mechanical Intelligence, Pure Mathematics, Morphogenesis and Mathematical Logic. Alan Mathison Turing (1912-1954) was a brilliant man who made major contributions in several areas of science. Today his name is mentioned frequently in philosophical discussions about the nature of Artificial Intelligence. Actually, he was a pioneer researcher in computer architecture and software engineering; his work in pure mathematics and mathematical logic extended considerably further and his last work, on morphogenesis in plants, is also acknowledged as being of the greatest originality and of permanent importance. He was one of the leading figures in Twentieth-century science, a fact which would have been known to the general public sooner but for the British Official Secrets Act, which prevented discussion of his wartime work. What is maybe surprising about these papers is that although they were written decades ago, they address major issues which concern researchers today.

This unique book succinctly summarizes the need to measure how ontologies (one of the building blocks of the Semantic Web) are currently being utilized, providing insights for various stakeholders. Where possible it improves and reuses terms in existing vocabularies/ontologies, as recommended by the Linked Data community. Recent advances in the Semantic Web have led to a proliferation of Resource Description Framework (RDF) data, which employ ontologies to semantically describe the information on the Web making it equally understandable for both humans and machines. However, to create a network effect, it is important that selective ontologies are used by more data publishers to improve the value of that ontology. For this to happen, it is vital to discover what is being used from an ontology to semantically annotate the information on the Web specific to a given domain. Answers to such basic but crucial questions can only be achieved by ascertaining how ontologies in the current semantic web are being utilized and adopted. The proposed frameworks to obtain such insights are explained with real-world examples to provide a clear and detailed description of ontology usage analysis. Both theoretical and practical, the book is of value to academics and professionals working in industry. Specifically, it is of primary interest to researchers, graduate students and practitioners in the area of the Semantic Web and its various real-world applications.

By presenting the latest advances in fuzzy sets and computing with words from around the globe, this book disseminates recent innovations in advanced intelligent technologies and systems. From intelligent control and intuitionistic fuzzy quantifiers to various data science and industrial applications, it includes a wide range of valuable lessons learned and ideas for future intelligent products and systems.

Graphic displays such as charts, graphs, diagrams, and maps play in important role today in the design and presentation of instructional materials education. There is also a strong need in scientific, technical and administrative fields to visually present facts, laws, principles etc. The increasing use of computer-based learning environments has also become an important field where the visual presentation of information plays a central role. Despite the importance of graphical displays as a means of communication and the fact that research about learning and cognition has advanced rapidly in the past two decades, the comprehension of graphics is still a rather unexplored area.

The comprehension of graphics is not only a stimulating topic in the fields of science and instructional psychology, but also in related disciplines such as semiotics, and artificial intelligence. Research on the comprehension of graphics complements the scientific investigation of cognitive processes in text comprehension, which has contributed much to our understanding of human cognition and learning. Ultimately, a better understanding of the cognitive processes involved in the comprehension of graphics will have an impact not only on cognitive theory, but also on educational practice.

The convergence of Artificial Intelligence (AI) in blockchain creates one of the world's most reliable technology-enabled decision-making systems that is virtually tamper-proof and provides solid insights and decisions. The integration of AI and Blockchain affects many aspects from food supply chain logistics and healthcare record sharing to media royalties and financial security. It is imperative that regulatory standards are emphasized in order to support positive outcomes from the integration of AI in blockchain technology. Regulatory Aspects of Artificial Intelligence on Blockchain provides relevant legal and security frameworks and the latest empirical research findings in blockchain and AI. Through the latest research and standards, the book identifies and offers solutions for overcoming legal consequences that pertain to the application of AI into the blockchain system, especially concerning the usage of smart contracts. The chapters, while investigating the legal and security issues associated with these applications, also include topics such as smart contacts, network vulnerability, cryptocurrency, machine learning, and more. This book is essential for technologists, security analysts, legal specialists, privacy and data security practitioners, IT consultants, standardization professionals, researchers, academicians, and students interested in blockchain and AI from a legal and security viewpoint.

This book presents the latest research of the field of optimization, modeling and algorithms, discussing the real-world application problems associated with new innovative methodologies. The requirements and demands of problem solving have been increasing exponentially and new computer science and engineering technologies have reduced the scope of data coverage worldwide. The recent advances in information communication technology (ICT) have contributed to reducing the gaps in the coverage of domains around the globe. The book is a valuable reference work for researchers in the fields of computer science and engineering with a particular focus on modeling, simulation and optimization as well as for postgraduates, managers, economists and decision makers

This book presents advances and innovations in grouping genetic algorithms, enriched with new and unique heuristic optimization techniques. These algorithms are specially designed for solving industrial grouping problems where system entities are to be partitioned or clustered into efficient groups according to a set of guiding decision criteria. Examples of such problems are: vehicle routing problems, team formation problems, timetabling problems, assembly line balancing, group maintenance planning, modular design, and task assignment. A wide range of industrial grouping problems, drawn from diverse fields such as logistics, supply chain management, project management, manufacturing systems, engineering design and healthcare, are presented. Typical complex industrial grouping problems, with multiple decision criteria and constraints, are clearly described using illustrative diagrams and formulations. The problems are mapped into a common group structure that can conveniently be used as an input scheme to specific variants of grouping genetic algorithms. Unique heuristic grouping techniques are developed to handle grouping problems efficiently and effectively. Illustrative examples and computational results are presented in tables and graphs to demonstrate the efficiency and effectiveness of the algorithms. Researchers, decision analysts, software developers, and graduate students from various disciplines will find this in-depth reader-friendly exposition of advances and applications of grouping genetic algorithms an interesting, informative and valuable resource.