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This contributed volume includes both theoretical research on philosophical logic and its applications in artificial intelligence, mostly employing the concepts and techniques of modal logic. It collects selected papers presented at the Second Asia Workshop on Philosophical Logic, held in Guangzhou, China in 2014, as well as a number of invited papers by specialists in related fields. The contributions represent pioneering philosophical logic research in Asia.
With all the material available in the field of artificial intelligence (AI) and soft computing-texts, monographs, and journal articles-there remains a serious gap in the literature. Until now, there has been no comprehensive resource accessible to a broad audience yet containing a depth and breadth of information that enables the reader to fully understand and readily apply AI and soft computing concepts.
Intelligent interactive multimedia systems and services will be ever more important in computer systems. Nowadays, computers are widespread and computer users range from highly qualified scientists to non-computer expert professionals. Therefore, designing dynamic personalization and adaptivity methods to store, process, transmit and retrieve information is critical for matching the technological progress with the consumer needs. This book contains the contributions presented at the eighth international KES conference on Intelligent Interactive Multimedia: Systems and Services, which took place in Sorrento, Italy, June 17-19, 2015. It contains 33 peer-reviewed scientific contributions that focus on issues ranging from intelligent image or video storage, retrieval, transmission and analysis to knowledge-based technologies, from advanced information technology architectures for video processing and transmission to advanced functionalities of information and knowledge-based services. We believe that this book will serve as a useful source of knowledge for both academia and industry, for all those faculty members, research scientists, scholars, Ph.D. students and practitioners, who are interested in fundamental and applied facets of intelligent interactive multimedia.
Proceedings of the 2015 Chinese Intelligent Automation Conference presents selected research papers from the CIAC'15, held in Fuzhou, China. The topics include adaptive control, fuzzy control, neural network based control, knowledge based control, hybrid intelligent control, learning control, evolutionary mechanism based control, multi-sensor integration, failure diagnosis, reconfigurable control, etc. Engineers and researchers from academia, industry and the government can gain valuable insights into interdisciplinary solutions in the field of intelligent automation.
This book constitutes the refereed proceedings of the 11th IFIP WG 5.11 International Symposium on Environmental Software Systems, ISESS 2015, held in Melbourne, Australia, in March 2015. The 62 revised full papers presented were carefully reviewed and selected from 104 submissions. The papers are organized in the following topical sections: information systems, information modeling and semantics; decision support tools and systems; modelling and simulation systems; architectures, infrastructures, platforms and services; requirements, software engineering and software tools; analytics and visualization; and high-performance computing and big data.
The eagerly anticipated updated resource on one of the most important areas of research and development: multi-agent systems
Multi-agent systems allow many intelligent agents to interact with each other, and this field of study has advanced at a rapid pace since the publication of the first edition of this book, which was nearly a decade ago. With this exciting new edition, the coverage of multi-agents is completely updated to include several areas that have come to prominence in the last several years, including auctions, computational social choice, and markov decision processes. In turn, a variety of topics that were initially considered critical have dwindled in importance, so the coverage of that subject matter is decreased with this new edition. The result of this redefined balance of coverage is a timely and essential resource on a popular topic.Introduces you to the concept of agents and multi-agent systems and the main applications for which they are appropriateDiscusses the main issues surrounding the design of intelligent agents and a multi-agent societyDelves into a number of typical applications for agent technologyAddresses deductive reasoning agents, practical reasoning agents, reactive and hybrid agents, and moreReviews multi-agent decision making, communication and cooperation, and intelligent autonomous agents
By the end of the book, you will have a firm grasp on how agents are distinct from other software paradigms and understand the characteristics of applications that lend themselves to agent-oriented software.
This book describes-in modern computer science terms-the Level II architecture of the meaning and definition of the process referred to as 'thinking'. It applies the basis of early cognitive science research to the creation of autonomous system architectures - connecting philosophical findings of the past with cutting-edge progress in artificial intelligence. Providing an in-depth introduction to the classical, philosophical theories of cognitive scientists like Immanuel Kant, Arthur Schopenhauer, and G.W.F. Hegel, the book examines the Will System, Reason System, Imagination System, and the Communication System.
A quantum computer is a computer based on a computational model which uses quantum mechanics, which is a subfield of physics to study phenomena at the micro level. There has been a growing interest on quantum computing in the 1990's and some quantum computers at the experimental level were recently implemented. Quantum computers enable super-speed computation and can solve some important problems whose solutions were regarded impossible or intractable with traditional computers.
This book provides a quick introduction to quantum computing for readers who have no backgrounds of both theory of computation and quantum mechanics. Elements of Quantum Computing presents the history, theories and engineering applications of quantum computing. The book is suitable to computer scientists, physicist and software engineers."
This book features a selection of papers presented at the First IFIP WG 12.6 International Workshop on Artificial Intelligence for Knowledge Management, AI4KM 2012, held in Montpellier, France, in August 2012, in conjunction with the 20th European Conference on Artificial Intelligence, ECAI 2012. The 11 revised and extended papers were carefully reviewed and selected for inclusion in this volume. They present new research and innovative aspects in the field of knowledge management.
This volume presents recent research on Methodologies and Intelligent Systems for Technology Enhanced Learning. It contains the contributions of ebuTEL 2013 conference which took place in Trento, Italy, on September, 16th 2013 and of mis4TEL 2014 conference, which took take place in Salamanca, Spain, on September, 4th-6th 2014.
This conference series are an open forumfor discussing intelligent systems for Technology Enhanced Learning and empirical methodologies for its design or evaluation."
The first and only book to systematically address methodologies and processes of leveraging non-traditional information sources in the context of investing and risk management Harnessing non-traditional data sources to generate alpha, analyze markets, and forecast risk is a subject of intense interest for financial professionals. A growing number of regularly-held conferences on alternative data are being established, complemented by an upsurge in new papers on the subject. Alternative data is starting to be steadily incorporated by conventional institutional investors and risk managers throughout the financial world. Methodologies to analyze and extract value from alternative data, guidance on how to source data and integrate data flows within existing systems is currently not treated in literature. Filling this significant gap in knowledge, The Book of Alternative Data is the first and only book to offer a coherent, systematic treatment of the subject. This groundbreaking volume provides readers with a roadmap for navigating the complexities of an array of alternative data sources, and delivers the appropriate techniques to analyze them. The authors--leading experts in financial modeling, machine learning, and quantitative research and analytics--employ a step-by-step approach to guide readers through the dense jungle of generated data. A first-of-its kind treatment of alternative data types, sources, and methodologies, this innovative book: Provides an integrated modeling approach to extract value from multiple types of datasets Treats the processes needed to make alternative data signals operational Helps investors and risk managers rethink how they engage with alternative datasets Features practical use case studies in many different financial markets and real-world techniques Describes how to avoid potential pitfalls and missteps in starting the alternative data journey Explains how to integrate information from different datasets to maximize informational value The Book of Alternative Data is an indispensable resource for anyone wishing to analyze or monetize different non-traditional datasets, including Chief Investment Officers, Chief Risk Officers, risk professionals, investment professionals, traders, economists, and machine learning developers and users.
The proceedings consists of 30 papers which have been selected and invited from the submissions to the "2nd International Conference on Computer Science, Applied Mathematics and Applications" (ICCSAMA 2014) held on 8-9 May, 2014 in Budapest, Hungary. The conference is organized into 7 sessions: Advanced Optimization Methods and Their Applications, Queueing Models and Performance Evaluation, Software Development and Testing, Computational Methods for Mobile and Wireless Networks, Computational Methods for Knowledge Engineering, Logic Based Methods for Decision Making and Data Mining and Nonlinear Systems and Applications, respectively. All chapters in the book discuss theoretical and practical issues connected with computational methods and optimization methods for knowledge engineering. The editors hope that this volume can be useful for graduate and Ph.D. students and researchers in Computer Science and Applied Mathematics. It is the hope of the editors that readers of this volume can find many inspiring ideas and use them to their research. Many such challenges are suggested by particular approaches and models presented in individual chapters of this book.
Thisbookistheproceedingsofthe5thAnnualConferenceonFuzzyInfor- tionandEngineering(ACFIE2010)fromSep. 23-27,2010in Huludao, China. The conference proceedings is published by Springer-Verlag (Advances in - telligent and Soft Computing, ISSN: 1867-5662). Thisyear, wehavereceivedmorethan191submissions.Eachpaperhas- dergonearigorousreviewprocess.Onlyhigh-qualitypapersareincluded.The 5thAnnualConferenceonFuzzyInformationandEngineering(ACFIE2010), built on the success of previous conferences, the ACFIE2005 (Guangzhou, China), is a major symposium for scientists, engineers and practitioners in China to present their updated results, ideas, developments and applications in all areas of fuzzy information and engineering. It aims to strengthen re- tions between industry research laboratories and universities, and to create a primary symposium for world scientistsinfuzzy?eldsasfollows: 1) The mathematical theory of fuzzy systems; 2) Fuzzy logic, systems and control; 3) Fuzzy optimization and decision-making; 4) Fuzzy information, identi?cation and clustering; 5) Fuzzy engineering application and soft computing method; etc. This book contains 89 papers, divided into ?ve main parts: In Section I, we have 15 papers on "the mathematical theory of fuzzy systems." In Section II, we have 15 papers on "fuzzy logic, systems and control." In Section III, we have 24 papers on "fuzzy optimization and decisi- making." In Section IV, we have 17 papers on "fuzzy information, identi?cation and clustering." In SectionV, wehave18 papers on"fuzzy engineeringapplicationandsoft computing method." VI Preface In addition to the large number of submissions, we are blessed with the presence of eight renowned keynote speakers and several distinguished p- elists and we shall organize workshops.
Computational intelligence aims to emulate aspects of biological systems for developing software and/or hardware that learns and adapts. Such systems primarily include neural networks, fuzzy logic systems and evolutionary computation each of them including multiple active and fast growing research directions. This book presents new and ground-breaking research from world-renowned experts focusing on various topics related to computational intelligence. What makes this book particularly interesting is the variety of subjects attained, which offer a global perspective on this central research field in the Knowledge Age.
Data science has never had more influence on the world. Large companies are now seeing the benefit of employing data scientists to interpret the vast amounts of data that now exists. However, the field is so new and is evolving so rapidly that the analysis produced can be haphazard at best. The 9 Pitfalls of Data Science shows us real-world examples of what can go wrong. Written to be an entertaining read, this invaluable guide investigates the all too common mistakes of data scientists - who can be plagued by lazy thinking, whims, hunches, and prejudices - and indicates how they have been at the root of many disasters, including the Great Recession. Gary Smith and Jay Cordes emphasise how scientific rigor and critical thinking skills are indispensable in this age of Big Data, as machines often find meaningless patterns that can lead to dangerous false conclusions. The 9 Pitfalls of Data Science is loaded with entertaining tales of both successful and misguided approaches to interpreting data, both grand successes and epic failures. These cautionary tales will not only help data scientists be more effective, but also help the public distinguish between good and bad data science.
Learn how to apply cognitive principles to the problems of computer vision Computational Models for Cognitive Vision formulates the computational models for the cognitive principles found in biological vision, and applies those models to computer vision tasks. Such principles include perceptual grouping, attention, visual quality and aesthetics, knowledge-based interpretation and learning, to name a few. The author's ultimate goal is to provide a framework for creation of a machine vision system with the capability and versatility of the human vision. Written by Dr. Hiranmay Ghosh, the book takes readers through the basic principles and the computational models for cognitive vision, Bayesian reasoning for perception and cognition, and other related topics, before establishing the relationship of cognitive vision with the multi-disciplinary field broadly referred to as "artificial intelligence". The principles are illustrated with diverse application examples in computer vision, such as computational photography, digital heritage and social robots. The author concludes with suggestions for future research and salient observations about the state of the field of cognitive vision. Other topics covered in the book include: - knowledge representation techniques - evolution of cognitive architectures - deep learning approaches for visual cognition Undergraduate students, graduate students, engineers, and researchers interested in cognitive vision will consider this an indispensable and practical resource in the development and study of computer vision.
This unique book on intelligence analysis covers several vital but often overlooked topics. It teaches the evidential and inferential issues involved in 'connecting the dots' to draw defensible and persuasive conclusions from masses of evidence: from observations we make, or questions we ask, we generate alternative hypotheses as explanations or answers; we make use of our hypotheses to generate new lines of inquiry and discover new evidence; and we test the hypotheses with the discovered evidence. To facilitate understanding of these issues and enable the performance of complex analyses, the book introduces an intelligent analytical tool, called Disciple-CD. Readers will practice with Disciple-CD and learn how to formulate hypotheses; develop arguments that reduce complex hypotheses to simpler ones; collect evidence to evaluate the simplest hypotheses; and assess the relevance and the believability of evidence, which combine in complex ways to determine its inferential force and the probabilities of the hypotheses.
This book reviews the state of the art in deep learning approaches to high-performance robust disease detection, robust and accurate organ segmentation in medical image computing (radiological and pathological imaging modalities), and the construction and mining of large-scale radiology databases. It particularly focuses on the application of convolutional neural networks, and on recurrent neural networks like LSTM, using numerous practical examples to complement the theory. The book's chief features are as follows: It highlights how deep neural networks can be used to address new questions and protocols, and to tackle current challenges in medical image computing; presents a comprehensive review of the latest research and literature; and describes a range of different methods that employ deep learning for object or landmark detection tasks in 2D and 3D medical imaging. In addition, the book examines a broad selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to text and image deep embedding for a large-scale chest x-ray image database; and discusses how deep learning relational graphs can be used to organize a sizable collection of radiology findings from real clinical practice, allowing semantic similarity-based retrieval.The intended reader of this edited book is a professional engineer, scientist or a graduate student who is able to comprehend general concepts of image processing, computer vision and medical image analysis. They can apply computer science and mathematical principles into problem solving practices. It may be necessary to have a certain level of familiarity with a number of more advanced subjects: image formation and enhancement, image understanding, visual recognition in medical applications, statistical learning, deep neural networks, structured prediction and image segmentation.
This book discusses data communication and computer networking, communication technologies and the applications of IoT (Internet of Things), big data, cloud computing and healthcare informatics. It explores, examines and critiques intelligent data communications and presents inventive methodologies in communication technologies and IoT. Aimed at researchers and academicians who need to understand the importance of data communication and advanced technologies in IoT, it offers different perspectives to help readers increase their knowledge and motivates them to conduct research in the area, highlighting various innovative ideas for future research.
This book discusses the basic requirements and constraints in building a brain-computer interaction system. These include the technical requirements for building the signal processing module and the acquisition module. The major aspects to be considered when designing a signal acquisition module for a brain-computer interaction system are the human brain, types and applications of brain-computer systems, and the basics of EEG (electroencephalogram) recording. The book also compares the algorithms that have been and that can be used to design the signal processing module of brain-computer interfaces, and describes the various EEG-acquisition devices available and compares their features and inadequacies. Further, it examines in detail the use of Emotiv EPOC (an EEG acquisition module developed by Emotiv) to build a complete brain-computer interaction system for driving robots using a neural network classification module.
This book discusses soft computing, which provides an efficient platform to deal with imprecision, uncertainty, vagueness and approximation in order to attain robustness and reliable computing. It explores two major concepts of soft computing: fuzzy set theory and neural networks, which relate to uncertainty handling and machine learning techniques respectively. Generally, fuzzy sets are considered as vague or uncertain sets having membership function lying between 0 and 1, and ANN is a type of artificial intelligence that attempts to imitate the way a human brain works by configuring specific applications, for instance pattern recognition or data classification, through learning processes. The book also presents C/MATLAB programming codes related to the basics of fuzzy set, interval arithmetic and ANN in a concise, practical and adaptable manner along, with simple examples and self-validation unsolved practice questions in few cases
The applications of Artificial Intelligence lie all around us; in our homes, schools and offices, in our cinemas, in art galleries and - not least - on the Internet. The results of Artificial Intelligence have been invaluable to biologists, psychologists, and linguists in helping to understand the processes of memory, learning, and language from a fresh angle. As a concept, Artificial Intelligence has fuelled and sharpened the philosophical debates concerning the nature of the mind, intelligence, and the uniqueness of human beings. Margaret A. Boden reviews the philosophical and technological challenges raised by Artificial Intelligence, considering whether programs could ever be really intelligent, creative or even conscious, and shows how the pursuit of Artificial Intelligence has helped us to appreciate how human and animal minds are possible.
In this book, the editors explain how students enrolled in two digital forensic courses at their institution are exposed to experiential learning opportunities, where the students acquire the knowledge and skills of the subject-matter while also learning how to adapt to the ever-changing digital forensic landscape. Their findings (e.g., forensic examination of different IoT devices) are also presented in the book. Digital forensics is a topic of increasing importance as our society becomes "smarter" with more of the "things" around us been internet- and inter-connected (e.g., Internet of Things (IoT) and smart home devices); thus, the increasing likelihood that we will need to acquire data from these things in a forensically sound manner. This book is of interest to both digital forensic educators and digital forensic practitioners, as well as students seeking to learn about digital forensics.
Looking for ways to handle the transition to a digital economy. Robots, artificial intelligence, and driverless cars are no longer things of the distant future. They are with us today and will become increasingly common in coming years, along with virtual reality and digital personal assistants. As these tools advance deeper into everyday use, they raise the question-how will they transform society, the economy, and politics? If companies need fewer workers due to automation and robotics, what happens to those who once held those jobs and don't have the skills for new jobs? And since many social benefits are delivered through jobs, how are people outside the workforce for a lengthy period of time going to earn a living and get health care and social benefits? Looking past today's headlines, political scientist and cultural observer Darrell M. West argues that society needs to rethink the concept of jobs, reconfigure the social contract, move toward a system of lifetime learning, and develop a new kind of politics that can deal with economic dislocations. With the U.S. governance system in shambles because of political polarization and hyper-partisanship, dealing creatively with the transition to a fully digital economy will vex political leaders and complicate the adoption of remedies that could ease the transition pain. It is imperative that we make major adjustments in how we think about work and the social contract in order to prevent society from spiraling out of control. This book presents a number of proposals to help people deal with the transition from an industrial to a digital economy. We must broaden the concept of employment to include volunteering and parenting and pay greater attention to the opportunities for leisure time. New forms of identity will be possible when the ""job"" no longer defines people's sense of personal meaning, and they engage in a broader range of activities. Workers will need help throughout their lifetimes to acquire new skills and develop new job capabilities. Political reforms will be necessary to reduce polarization and restore civility so there can be open and healthy debate about where responsibility lies for economic well-being. This book is an important contribution to a discussion about tomorrow-one that needs to take place today.
Social Signal Processing is the first book to cover all aspects of the modeling, automated detection, analysis, and synthesis of nonverbal behavior in human-human and human-machine interactions. Authoritative surveys address conceptual foundations, machine analysis and synthesis of social signal processing, and applications. Foundational topics include affect perception and interpersonal coordination in communication; later chapters cover technologies for automatic detection and understanding such as computational paralinguistics and facial expression analysis and for the generation of artificial social signals such as social robots and artificial agents. The final section covers a broad spectrum of applications based on social signal processing in healthcare, deception detection, and digital cities, including detection of developmental diseases and analysis of small groups. Each chapter offers a basic introduction to its topic, accessible to students and other newcomers, and then outlines challenges and future perspectives for the benefit of experienced researchers and practitioners in the field.
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