Sound waves propagate through various media, and allow communication or entertainment for us, humans. Music we hear or create can be perceived in such aspects as rhythm, melody, harmony, timbre, or mood. All these elements of music can be of interest for users of music information retrieval systems. Since vast music repositories are available for everyone in everyday use (both in private collections, and in the Internet), it is desirable and becomes necessary to browse music collections by contents. Therefore, music information retrieval can be potentially of interest for every user of computers and the Internet. There is a lot of research performed in music information retrieval domain, and the outcomes, as well as trends in this research, are certainly worth popularizing. This idea motivated us to prepare the book on Advances in Music Information Retrieval.

It is divided into four sections: MIR Methods and Platforms, Harmony, Music Similarity, and Content Based Identification and Retrieval. Glossary of basic terms is given at the end of the book, to familiarize readers with vocabulary referring to music information retrieval.

One of the most challenging issues for the intelligent decision systems is to effectively manage the large-scale complex distributed environments such as computational clouds, grids, ad hoc and P2P networks, under the different types of users, their relations, and real-world uncertainties. In this context the IT resources and services usually belong to different owners (institutions, enterprises, or individuals) and are managed by different administrators. These administrators conform to different sets of rules and configuration directives, and can impose different usage policies on the system users. Additionally, uncertainties are presented in various types of information that are incomplete, imprecise, fragmentary or overloading, which hinders the full and precise determination of the evaluation criteria, their subsequent and selection, the assignment scores, and eventually the final integrated decision result.

This book presents new ideas, analysis, implementations and evaluation of the next generation intelligent techniques for solving complex decision problems in large-scale distributed systems. In 15 chapters several important formulations of the decision problems in heterogeneous environments are identified and a review of the recent approaches, from game theoretical models and computational intelligent techniques, such as genetic, memetic and evolutionary algorithms, to intelligent multi-agent systems and networking are presented. We believe that this volume will serve as a reference for the students, researchers and industry practitioners working in or are interested in joining interdisciplinary works in the areas of intelligent decision systems using emergent distributed computing paradigms. It will also allow newcomers to grasp key concerns and potential solutions on the selected topics."

This monograph is devoted to the theory and development of autonomous navigation of mobile robots using computer vision based sensing mechanism. The conventional robot navigation systems, utilizing traditional sensors like ultrasonic, IR, GPS, laser sensors etc., suffer several drawbacks related to either the physical limitations of the sensor or incur high cost. Vision sensing has emerged as a popular alternative where cameras can be used to reduce the overall cost, maintaining high degree of intelligence, flexibility and robustness.

This book includes a detailed description of several new approaches for real life vision based autonomous navigation algorithms and SLAM. It presents the concept of how subgoal based goal-driven navigation can be carried out using vision sensing. The development concept of vision based robots for path/line tracking using fuzzy logic is presented, as well as how a low-cost robot can be indigenously developed in the laboratory with microcontroller based sensor systems. The book describes successful implementation of integration of low-cost, external peripherals, with off-the-shelf procured robots. An important highlight of the book is that it presents a detailed, step-by-step sample demonstration of how vision-based navigation modules can be actually implemented in real life, under 32-bit Windows environment. The book also discusses the concept of implementing vision based SLAM employing a two camera based system.

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Robotic Sailing 2017. This book contains the peer-reviewed papers presented at the 10th International Robotic Sailing Conference which was organized in conjunction with the 10th World Robotic Sailing Championship held in Horten, Norway the 4th-9th of September 2017. The seven papers cover topics of interest for autonomous robotic sailing which represents some of the most challenging research and development areas. The book is divided into two parts. The first part contains papers which focus on the design of sails and software for the assessment and predication of sailboat performance as well as software platforms and middleware for sailboat competition and research. The second part includes algorithms and strategies for navigation and collision avoidance on local, mid- and long range. The differences in approach in the included papers show that robotic sailing is still an emerging cross-disciplinary science. The multitude of suggestions to the specific problems of prediction and simulation of sailboats as well as the challenges of route planning, anti-grounding and collision avoidance are good indicators of science in its infancy. Hence, we may expect the future to hold great advances for robotic sailing.

By the dawn of the new millennium, robotics has undergone a major tra- formation in scope and dimensions. This expansion has been brought about bythematurityofthe?eldandtheadvancesinitsrelatedtechnologies.From a largely dominant industrial focus, robotics has been rapidly expanding into the challenges of the human world. The new generation of robots is expected to safely and dependably co-habitat with humans in homes, workplaces, and communities, providingsupportinservices, entertainment, education, heal- care, manufacturing, and assistance. Beyond its impact on physical robots, the body of knowledge robotics has produced is revealing a much wider range of applications reaching across - verse research areas and scienti?c disciplines, such as: biomechanics, haptics, neurosciences, virtual simulation, animation, surgery, and sensor networks among others. In return, the challenges of the new emerging areas are pr- ing an abundant source of stimulation and insights for the ?eld of robotics. It is indeed at the intersection of disciplines that the most striking advances happen. The goal of the series of Springer Tracts in Advanced Robotics (STAR) is to bring, in a timely fashion, the latest advances and developments in robotics on the basis of their signi?cance and quality. It is our hope that the wider dissemination of research developments will stimulate more exchanges and collaborations among the research community and contribute to further advancement of this rapidly growing ?

Optimization is an integral part to science and engineering. Most real-world applications involve complex optimization processes, which are di?cult to solve without advanced computational tools. With the increasing challenges of ful?lling optimization goals of current applications there is a strong drive to advancethe developmentofe?cientoptimizers. The challengesintroduced by emerging problems include: * objective functions which are prohibitively expensive to evaluate, so ty- callysoonlyasmallnumber ofobjectivefunctionevaluationscanbemade during the entire search, * objective functions which are highly multimodal or discontinuous, and * non-stationary problems which may change in time (dynamic). Classical optimizers may perform poorly or even may fail to produce any improvement over the starting vector in the face of such challenges. This has motivated researchers to explore the use computational intelligence (CI) to augment classical methods in tackling such challenging problems. Such methods include population-based search methods such as: a) evolutionary algorithms and particle swarm optimization and b) non-linear mapping and knowledgeembedding approachessuchasarti?cialneuralnetworksandfuzzy logic, to name a few. Such approaches have been shown to perform well in challenging settings. Speci?cally, CI are powerful tools which o?er several potential bene?ts such as: a) robustness (impose little or no requirements on the objective function) b) versatility (handle highly non-linear mappings) c) self-adaptionto improveperformance and d) operationin parallel(making it easy to decompose complex tasks). However, the successful application of CI methods to real-world problems is not straightforward and requires both expert knowledge and trial-and-error experiments.

This carefully edited book is putting emphasis on computational and artificial intelligent methods for learning and their relative applications in robotics, embedded systems, and ICT interfaces for psychological and neurological diseases. The book is a follow-up of the scientific workshop on Neural Networks (WIRN 2015) held in Vietri sul Mare, Italy, from the 20th to the 22nd of May 2015. The workshop, at its 27th edition became a traditional scientific event that brought together scientists from many countries, and several scientific disciplines. Each chapter is an extended version of the original contribution presented at the workshop, and together with the reviewers' peer revisions it also benefits from the live discussion during the presentation. The content of book is organized in the following sections. 1. Introduction, 2. Machine Learning, 3. Artificial Neural Networks: Algorithms and models, 4. Intelligent Cyberphysical and Embedded System, 5. Computational Intelligence Methods for Biomedical ICT in Neurological Diseases, 6. Neural Networks-Based Approaches to Industrial Processes, 7. Reconfigurable Modular Adaptive Smart Robotic Systems for Optoelectronics Industry: The White'R Instantiation This book is unique in proposing a holistic and multidisciplinary approach to implement autonomous, and complex Human Computer Interfaces.

After an introduction to renewable energy technologies, the authors present computational intelligence techniques for optimizing the manufacture of related technologies, including solar concentrators. In particular the authors present new applications for their neural classifiers for image and pattern recognition. The book will be of interest to researchers in computational intelligence, in particular in the domain of neural networks, and engineers engaged with renewable energy technologies.

This book introduces a novel approach to discrete optimization, providing both theoretical insights and algorithmic developments that lead to improvements over state-of-the-art technology. The authors present chapters on the use of decision diagrams for combinatorial optimization and constraint programming, with attention to general-purpose solution methods as well as problem-specific techniques. The book will be useful for researchers and practitioners in discrete optimization and constraint programming. "Decision Diagrams for Optimization is one of the most exciting developments emerging from constraint programming in recent years. This book is a compelling summary of existing results in this space and a must-read for optimizers around the world." [Pascal Van Hentenryck]

This monograph originates from my work on the HAPTEX project. In - cember 2004 Prof. Franz-Erich Wolter, the head of the Institute of Man- Machine Communication of the Leibniz Universit. at Hannover, o?ered me the opportunity to participate in that EU funded project. Being a mat- matician I had only very little experience in the ?eld of haptic simulation in those days, but Prof. Wolter trusted in my ability to become acquainted with new ?elds of research in a very short time. I am still thankful for the con?dence he has shown me. Since then I indeed learned and found out a lot. With this monograph I try to pass on the knowledge I gained. Having a reader in mind who-like me at the beginning of the project-has no background in psychophysics, neurophysiologyortextileengineeringIwillprovidethenecessarybasics.The skilled reader may safely skip these parts. Nevertheless I presume some basic knowledge in mathematics. I hope that this thesis might help a newcomer to discover the fascinating ?eld of tactile simulation. This workwouldnot havebeen possible without the funding of the project "HAPtic sensing of virtual TEXtiles" (HAPTEX) under the Sixth Fra- work Programme (FP6) of the European Union (Contract No. IST-6549).

After I came to know Jerne's network theory on the immune system, I became fascinated with the immune system as an information system. The main pro totypes for biological information systems have been the neural systems and the brain. However, the immune system is not only an interesting informa tion system but it may provide a design paradigm for artificial information systems. With such a consideration, I initiated a project titled "autonomous decentralized recognition mechanism of the immune network and its applica tion to distributed information processing" in 1990 under a Grant-in-Aid for Scientific Research on a Priority Area ("Autonomous Distributed Systems") supported by the Ministry of Education, Science, and Culture. During the project, I promoted the idea that the immune system could be a prototype of autonomous distributed systems. After the project, we organized an international workshop on immunity based systems in 1996 in conjunction with the International Conference on Multi-Agent Systems held in Kyoto, Japan. Recently, there have been several international conferences related to topics inspired by the immune system and an increasing number of research papers related to the topic. In writing this book, a decade after the project, I still believe that the immune system can be a prototype, a compact but sophisticated system that nature has shown us for building artificial information systems in this network age of the twenty-first century."

This book presents recent advances in the field of intelligent systems. Composed of fourteen selected chapters, it covers a wide range of research that varies from applications in industrial data science to those in applied science. Today the word INNOVATION is more and more connected with the words INTELLIGENT and SECURITY, as such the book discusses the theory and applications of hot topics such as big data, education applications of robots with different levels of autonomy, knowledge-based modeling and control of complex dynamical systems, sign-based synthesis of behavior, security issues with intelligent systems, innovative intelligent control design, neuromorphic computation, data-driven classification, intelligent modeling and measurement innovations, multisensor data association, personal education assistants, a modern production architecture, study of peer review and scientometrics, intelligent research on bug report data, and clustering non-Gaussian data. The broad and varied research discussed represents the mainstream of contemporary intelligent innovations that are slowly but surely changing the world.

Machine learning is an emerging area of computer science that deals with the design and development of new algorithms based on various types of data. Machine Learning Algorithms for Problem Solving in Computational Applications: Intelligent Techniques addresses the complex realm of machine learning and its applications for solving various real-world problems in a variety of disciplines, such as manufacturing, business, information retrieval, and security. This premier reference source is essential for professors, researchers, and students in artificial intelligence as well as computer science and engineering.

This scholarly book presents and critically evaluates the outstanding contributions of both cognitive psychology and artificial intelligence to our understanding of the nature of intelligence and intelligent systems. Examining conceptual thought across the domains of reasoning and logic, language and analogy, and scientific discovery, Wagman compares human reasoning with computer reasoning. Of special interest to readers is the general critique of artificial intelligence research directed toward the ultimate objective of mapping and surpassing all of human knowledge.

The first chapter examines the theoretical foundations of the logical approach to artificial intelligence and the centrality of declarative knowledge and the predicate calculus. The artifical intelligence system, CYC, is critically examined with respect to its avowed objective of matching or surpassing human intelligence. The second chapter focuses on the probabilistic contrast model of causal reasoning and underscores its significance as a mathematical conceptualization of human reasoning. In the third chapter, the ARCS (Analogical Retrieval by Constraint Satisfaction) system is discussed and its psychological validity is evaluated. In the fourth chapter, scientific heuristics characteristics of different developmental levels and differentially applied in the discovery spaces of hypotheses and experiments are analyzed in the context of the philosophy of science. The fifth chapter presents the logic, principles, and applications of PAULINE, a pragmatic language generation system and explains human language pragmatics.

This book describes how evolutionary algorithms (EA), including genetic algorithms (GA) and particle swarm optimization (PSO) can be utilized for solving multi-objective optimization problems in the area of embedded and VLSI system design. Many complex engineering optimization problems can be modelled as multi-objective formulations. This book provides an introduction to multi-objective optimization using meta-heuristic algorithms, GA and PSO and how they can be applied to problems like hardware/software partitioning in embedded systems, circuit partitioning in VLSI, design of operational amplifiers in analog VLSI, design space exploration in high-level synthesis, delay fault testing in VLSI testing and scheduling in heterogeneous distributed systems. It is shown how, in each case, the various aspects of the EA, namely its representation and operators like crossover, mutation, etc, can be separately formulated to solve these problems. This book is intended for design engineers and researchers in the field of VLSI and embedded system design. The book introduces the multi-objective GA and PSO in a simple and easily understandable way that will appeal to introductory readers.

This book includes extended versions of selected works presented at the 52nd Annual Convention of Computer Society of India (CSI 2017), held at Science City, Kolkata on 19-21 January 2018. It features a collection of chapters focusing on recent trends in computational intelligence, covering topics such as ANN, neuro-fuzzy based clustering, edge detection, data mining, mobile cloud computing, intelligent scheduling, processing and authentication. It also discusses societal applications of these methods. As such it is useful for students, researchers and industry professionals working in the area of computational intelligence.

Linking Government Data provides a practical approach to addressing common information management issues. The approaches taken are based on international standards of the World Wide Web Consortium. Linking Government Data gives both the costs and benefits of using linked data techniques with government data; describes how agencies can fulfill their missions with less cost; and recommends how intra-agency culture must change to allow public presentation of linked data. Case studies from early adopters of linked data approaches in international governments are presented in the last section of the book. Linking Government Data is designed as a professional book for those working in Semantic Web research and standards development, and for early adopters of Semantic Web standards and techniques. Enterprise architects, project managers and application developers in commercial, not-for-profit and government organizations concerned with scalability, flexibility and robustness of information management systems will also find this book valuable. Students focused on computer science and business management will also find value in this book.

When no samples are available to estimate a probability distribution, we have to invite some domain experts to evaluate the belief degree that each event will happen. Perhaps some people think that the belief degree should be modeled by subjective probability or fuzzy set theory. However, it is usually inappropriate because both of them may lead to counterintuitive results in this case. In order to rationally deal with belief degrees, uncertainty theory was founded in 2007 and subsequently studied by many researchers. Nowadays, uncertainty theory has become a branch of axiomatic mathematics for modeling belief degrees. This is an introductory textbook on uncertainty theory, uncertain programming, uncertain statistics, uncertain risk analysis, uncertain reliability analysis, uncertain set, uncertain logic, uncertain inference, uncertain process, uncertain calculus, and uncertain differential equation. This textbook also shows applications of uncertainty theory to scheduling, logistics, networks, data mining, control, and finance.

The unexpected and premature passing away of Professor Ebrahim H. "Abe" Mamdani on January, 22, 2010, was a big shock to the scientific community, to all his friends and colleagues around the world, and to his close relatives. Professor Mamdani was a remarkable figure in the academic world, as he contributed to so many areas of science and technology. Of great relevance are his latest thoughts and ideas on the study of language and its handling by computers. The fuzzy logic community is particularly indebted to Abe Mamdani (1941-2010) who, in 1975, in his famous paper An Experiment in Linguistic Synthesis with a Fuzzy Logic Controller, jointly written with his student Sedrak Assilian, introduced the novel idea of fuzzy control. This was an elegant engineering approach to the modeling and control of complex processes for which mathematical models were unknown or too difficult to build, yet they could effectively and efficiently be controlled by human operators. This ground-breaking idea has found innumerable applications and can be considered as one of the main factors for the proliferation and adoption of fuzzy logic technology. Professor Mamdani's own life and vital experience are illustrative of his "never surrendering" attitude while facing adversaries, which is normal for a person proposing any novel solution, and represent a great example for everybody. His subtle sense of humor, his joy for life, and his will to critically help people, especially young people, were characteristics deeply appreciated by all the people who enjoyed and benefited from his friendship and advice. This book constitutes a posthumous homage to Abe Mamdani. It is a collection of original papers related in some way to his works, ideas and vision, and especially written by researchers directly acquainted with him or with his work. The underlying goal of this book will be fulfilled if, in the very spirit of Mamdani's legacy, the papers will trigger a scientific or philosophical debate on the issues covered, or contribute to a cross-fertilization of ideas in the various fields.

This book brings together historical notes, reviews of research developments, fresh ideas on how to make VC (Vapnik-Chervonenkis) guarantees tighter, and new technical contributions in the areas of machine learning, statistical inference, classification, algorithmic statistics, and pattern recognition. The contributors are leading scientists in domains such as statistics, mathematics, and theoretical computer science, and the book will be of interest to researchers and graduate students in these domains.

Mobile agents are software nomads that act as your personal representative, working autonomously through networks. They are able to visit network nodes directly using available computing power and are not limited by platform. This emerging field is now poised to become a cornerstone for new Web-based ubiquitous computing environments. Mobile Agents provides a practical introduction to mobile agent technology and surveys the state of the art in mobile agent research. Students and researchers can use the book as an introduction to the concepts and possibilities of this field and as an overview of ongoing research. Developers can use it to identify the capabilities of the technology to decide if mobile agents are the right solution for them. Practioners can also gain hands-on experience in programming mobile agents through exploration of the source code for a complete mobile agent environment available through the companion website.
*Summarizes the state of the art in mobile agent research
*Identifies the benefits and limitations of current mobile agent technology to help developers understand the possibilities of this new field
*Extensive mobile agents web portal ("www.mobile-agents.org") with the Java source code for a complete industrial-quality environment for mobile agents, with significant parts of the system open source

Bayesian networks are now being used in a variety of artificial intelligence applications. These networks are high-level representations of probability distributions over a set of variables that are used for building a model of the problem domain. ""Bayesian Network Technologies: Applications and Graphical Models"" provides an excellent and well-balanced collection of areas where Bayesian networks have been successfully applied. This book describes the underlying concepts of Bayesian Networks in an interesting manner with the help of diverse applications, and theories that prove Bayesian networks valid. ""Bayesian Network Technologies: Applications and Graphical Models"" provides specific examples of how Bayesian networks are powerful machine learning tools critical in solving real-life problems.

Singularity Hypotheses: A Scientific and Philosophical Assessment offers authoritative, jargon-free essays and critical commentaries on accelerating technological progress and the notion of technological singularity. It focuses on conjectures about the intelligence explosion, transhumanism, and whole brain emulation. Recent years have seen a plethora of forecasts about the profound, disruptive impact that is likely to result from further progress in these areas. Many commentators however doubt the scientific rigor of these forecasts, rejecting them as speculative and unfounded. We therefore invited prominent computer scientists, physicists, philosophers, biologists, economists and other thinkers to assess the singularity hypotheses. Their contributions go beyond speculation, providing deep insights into the main issues and a balanced picture of the debate.

Artificial Intelligence and Security in Computing Systems is a peer-reviewed conference volume focusing on three areas of practice and research progress in information technologies:

-Methods of Artificial Intelligence presents methods and algorithms which are the basis for applications of artificial intelligence environments.
-Multiagent Systems include laboratory research on multiagent intelligent systems as well as upon their applications in transportation and information systems.
-Computer Security and Safety presents techniques and algorithms which will be of great interest to practitioners. In general, they focus on new cryptographic algorithms (including a symmetric key encryption scheme, hash functions, secret generation and sharing schemes, and secure data storage), a formal language for policy access control description and its implementation, and risk management methods (used for continuous analysis both in distributed network and software development projects).