This book presents comprehensive coverage of the latest advances in research into enabling machines to listen to and compose new music. It includes chapters introducing what we know about human musical intelligence and on how this knowledge can be simulated with AI. The development of interactive musical robots and emerging new approaches to AI-based musical creativity are also introduced, including brain-computer music interfaces, bio-processors and quantum computing. Artificial Intelligence (AI) technology permeates the music industry, from management systems for recording studios to recommendation systems for online commercialization of music through the Internet. Yet whereas AI for online music distribution is well advanced, this book focuses on a largely unexplored application: AI for creating the actual musical content.

Knowing our World: An Artificial Intelligence Perspective considers the methodologies of science, computation, and artificial intelligence to explore how we humans come to understand and operate in our world. While humankind's history of articulating ideas and building machines that can replicate the activity of the human brain is impressive, Professor Luger focuses on understanding the skills that enable these goals. Based on insights afforded by the challenges of AI design and program building, Knowing our World proposes a foundation for the science of epistemology. Taking an interdisciplinary perspective, the book demonstrates that AI technology offers many representational structures and reasoning strategies that support clarification of these epistemic foundations. This monograph is organized in three Parts; the first three chapters introduce the reader to the foundations of computing and the philosophical background that supports the AI tradition. These three chapters describe the origins of AI, programming as iterative refinement, and the representations and very high-level language tools that support AI application building. The book's second Part introduces three of the four paradigms that represent research and development in AI over the past seventy years: the symbol-based, connectionist, and complex adaptive systems. Luger presents several introductory programs in each area and demonstrates their use. The final three chapters present the primary theme of the book: bringing together the rationalist, empiricist, and pragmatist philosophical traditions in the context of a Bayesian world view. Luger describes Bayes' theorem with a simple proof to demonstrate epistemic insights. He describes research in model building and refinement and several philosophical issues that constrain the future growth of AI. The book concludes with his proposal of the epistemic stance of an active, pragmatic, model-revising realism.

This book features a selection of extended papers presented at the 8th IFIP WG 12.6 International Workshop on Artificial Intelligence for Knowledge Management, AI4KM 2021, held in Yokohama, Japan, in January 2021, in the framework of the International Joint Conference on Artificial Intelligence, IJCAI 2020.*The 14 revised and extended papers presented together with an invited talk were carefully reviewed and selected for inclusion in this volume. They present new research and innovative aspects in the field of knowledge management and discuss methodological, technical and organizational aspects of artificial intelligence used for knowledge management. *The workshop was held virtually.

This book comprises refereed papers presented at The International Conference on Artificial Intelligence and Power Engineering (AIPE2020), held in Moscow, Russia, on December 25-27, 2020. The book's/conference's general scope covers the latest advances for the development of artificial intelligence systems and their applications in various fields from power engineering to biology and education. Given the rapid development of artificial intelligence systems, the book emphasizes the need for the intensification of training of a growing number of relevant specialists, in particular, in energy and power engineering to increase the effectiveness of creation and diagnosing of appropriate technical solutions. In digital artificial intelligence systems, scientists endeavor to reproduce the innate intellectual abilities of humans and other organisms. The in-depth study of biological and self-organizing systems provides new approaches to create more and more effective artificial intelligence methods. Topics of the included papers concern thematic materials in the following spheres: mathematics and computer algorithms; analysis of some technical solutions; technological and educational approaches. The book is a compilation of state-of-the-art papers in the field, covering a comprehensive range of subjects that are relevant to business managers and engineering professionals alike. The breadth and depth of these proceedings make them an excellent resource for asset management practitioners, researchers, and academics, as well as undergraduate and postgraduate students interested in artificial intelligence systems and their growing applications. The intended readership includes specialists, students, and other circles of readers who would like to know where artificial intelligence systems can be applied in the future with great benefit.

The 3-volume set CCIS 1422, CCIS 1423 and CCIS 1424 constitutes the refereed proceedings of the 7th International Conference on Artificial Intelligence and Security, ICAIS 2021, which was held in Dublin, Ireland, in July 2021. The total of 131 full papers and 52 short papers presented in this 3-volume proceedings was carefully reviewed and selected from 1013 submissions. The papers were organized in topical sections as follows: Part I: artificial intelligence; Part II: artificial intelligence; big data; cloud computing and security; Part III: cloud computing and security; encryption and cybersecurity; information hiding; IoT security.

This book presents best selected research papers presented at the 3rd International Conference on Cognitive Informatics and Soft Computing (CISC 2020), held at Balasore College of Engineering & Technology, Balasore, Odisha, India, from 12 to 13 December 2020. It highlights, in particular, innovative research in the fields of cognitive informatics, cognitive computing, computational intelligence, advanced computing, and hybrid intelligent models and applications. New algorithms and methods in a variety of fields are presented, together with solution-based approaches. The topics addressed include various theoretical aspects and applications of computer science, artificial intelligence, cybernetics, automation control theory, and software engineering.

This volume seeks to leverage academic interdisciplinarity to develop insight into how Artificial intelligence (AI), the latest GPT to emerge, may influence or radically change socio-political norms, practices, and institutions. AI may best be understood as a predictive technology. "Prediction is the process of filling in missing information. Prediction takes information you have, often called 'data', and uses it to generate information you don't have" (Agrawal, Gans, and Goldfarb 2018, 13; also see Mayer-Schonberger and Ramge 2018). AI makes prediction cheap because the cost of information is now close to zero. Cheap prediction through AI technologies are radically altering how we govern ourselves, interact with each other, and sustain society. Contributors to this volume represent the academic disciplines of Sociology and Political Science working within a diverse set of intra-disciplinary fields that when combined, yield novel insights into the following questions guiding this volume: How might AI transform people? How might AI transform socio-political practices? How might AI transform socio-political institutions?

Digital Twins for Healthcare: Design, Challenges and Solutions establishes the state-of-art in the specification, design, creation, deployment and exploitation of digital twins' technologies for healthcare and wellbeing. A digital twin is a digital replication of a living or non-living physical entity. When data is transmitted seamlessly, it bridges the physical and virtual worlds, thus allowing the virtual entity to exist simultaneously with the physical entity. A digital twin facilitates the means to understand, monitor, and optimize the functions of the physical entity and provide continuous feedback. It can be used to improve citizens' quality of life and wellbeing in smart cities and the virtualization of industrial processes.

This book discusses feature engineering and computational intelligence solutions for ECG monitoring, with a particular focus on how these methods can be efficiently used to address the emerging challenges of dynamic, continuous & long-term individual ECG monitoring and real-time feedback. By doing so, it provides a "snapshot" of the current research at the interface between physiological signal analysis and machine learning. It also helps clarify a number of dilemmas and encourages further investigations in this field, to explore rational applications of feature engineering and computational intelligence in ECG monitoring. The book is intended for researchers and graduate students in the field of biomedical engineering, ECG signal processing, and intelligent healthcare.

This book is a collection of research papers presented at the International Workshop on Intelligent Software Engineering Automation (ISEA 2020) in the 27th Asia-Pacific Software Engineering Conference (APSEC 2020), during 1-4 December 2020 in Singapore. The book discusses automated tools and techniques which are required to reflect over business knowledge to identify what is missing or could be effectively changed while producing and evolving. The book presents works from international researchers and practitioners in the fields of intelligent software engineering/automated software engineering to discuss applications, experiences, and emerging advanced techniques.

Learn how AI impacts the healthcare ecosystem through real-life case studies with TensorFlow 2.0 and other machine learning (ML) libraries. This book begins by explaining the dynamics of the healthcare market, including the role of stakeholders such as healthcare professionals, patients, and payers. Then it moves into the case studies. The case studies start with EHR data and how you can account for sub-populations using a multi-task setup when you are working on any downstream task. You also will try to predict ICD-9 codes using the same data. You will study transformer models. And you will be exposed to the challenges of applying modern ML techniques to highly sensitive data in healthcare using federated learning. You will look at semi-supervised approaches that are used in a low training data setting, a case very often observed in specialized domains such as healthcare. You will be introduced to applications of advanced topics such as the graph convolutional network and how you can develop and optimize image analysis pipelines when using 2D and 3D medical images. The concluding section shows you how to build and design a closed-domain Q&A system with paraphrasing, re-ranking, and strong QnA setup. And, lastly, after discussing how web and server technologies have come to make scaling and deploying easy, an ML app is deployed for the world to see with Docker using Flask. By the end of this book, you will have a clear understanding of how the healthcare system works and how to apply ML and deep learning tools and techniques to the healthcare industry. What You Will Learn Get complete, clear, and comprehensive coverage of algorithms and techniques related to case studies Look at different problem areas within the healthcare industry and solve them in a code-first approach Explore and understand advanced topics such as multi-task learning, transformers, and graph convolutional networks Understand the industry and learn ML Who This Book Is For Data scientists and software developers interested in machine learning and its application in the healthcare industry

This book is devoted to the leading research in applying learning automaton (LA) and heuristics for solving benchmark and real-world optimization problems. The ever-increasing application of the LA as a promising reinforcement learning technique in artificial intelligence makes it necessary to provide scholars, scientists, and engineers with a practical discussion on LA solutions for optimization. The book starts with a brief introduction to LA models for optimization. Afterward, the research areas related to LA and optimization are addressed as bibliometric network analysis. Then, LA's application in behavior control in evolutionary computation, and memetic models of object migration automata and cellular learning automata for solving NP hard problems are considered. Next, an overview of multi-population methods for DOPs, LA's application in dynamic optimization problems (DOPs), and the function evaluation management in evolutionary multi-population for DOPs are discussed. Highlighted benefits * Presents the latest advances in learning automata-based optimization approaches. * Addresses the memetic models of learning automata for solving NP-hard problems. * Discusses the application of learning automata for behavior control in evolutionary computation in detail. * Gives the fundamental principles and analyses of the different concepts associated with multi-population methods for dynamic optimization problems.

This book studies how autonomous aerial robots physically interact with the surrounding environment. Intended to promote the advancement of aerial physical interaction, it analyzes a particular class of aerial robots: tethered aerial vehicles. By examining specific systems, while still considering the challenges of the general problem, it will help readers acquire the knowledge and expertise needed for the subsequent development of more general methods applicable to aerial physical interaction. The formal analysis covers topics ranging from control, state estimation, and motion planning, to experimental validation. Addressing both theoretical and technical aspects, the book is intended for a broad academic and industrial readership, including undergraduate students, researchers and engineers. It can be used as a teaching reference, or as the basis for product development.

This book contains the proceedings of the 17th International Conference on Computing and Information Technology (IC2IT2021) that was held during May 13-14, 2021, in Bangkok, Thailand. The research contributions include machine learning, natural language processing, image processing, intelligent systems and algorithms, as well as network and cloud computing. These lead to the major research directions for emerging information technology and innovation, reflecting digital disruption in the world.

This book constitutes the refereed proceedings of six International Workshops held as parallel events of the 17th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2021, virtually and in Hersonissos, Crete, Greece, in June 2021: the 6th Workshop on 5G-Putting Intelligence to the Network Edge, 5G-PINE 2021; Artificial Intelligence in Biomedical Engineering and Informatics Workshop, AI-BIO 2021; Workshop on Defense Applications of AI, DAAI 2021; Distributed AI for Resource-Constrained Platforms Workshop, DARE 2021; Energy Efficiency and Artificial Intelligence Workshop, EEAI 2021; and the 10th Mining Humanistic Data Workshop, MHDW 2021. The 24 full papers and 16 short papers presented at these workshops were carefully reviewed and selected from 72 submissions. The papers presented at 5G-PINE focus on the latest AI applications in the telecommunication industry and AI in modern 5G-oriented telecommunications infrastructures. The papers chosen for AI-BIO 2021 present research on the subject of AI, in its broadest sense, in biomedical engineering and health informatics. The DAAI 2021 papers aim at presenting recent evolutions in artificial intelligence applicable to defense and security applications. The papers selected for DARE 2021 address a variety of pertinent and challenging topics within the scope of distributed AI for resource-constrained platforms. The papers presented at EEAI 2021 aim to bring together interdisciplinary approaches that focus on the application of AI-driven solutions for increasing and improving energy efficiency of residential and tertiary buildings and of occupant behavior. The MHDW papers focus on topics such as recommendation systems, sentiment analysis, pattern recognition, data mining, and time series.

This book presents the concept of the double hierarchy linguistic term set and its extensions, which can deal with dynamic and complex decision-making problems. With the rapid development of science and technology and the acceleration of information updating, the complexity of decision-making problems has become increasingly obvious. This book provides a comprehensive and systematic introduction to the latest research in the field, including measurement methods, consistency methods, group consensus and large-scale group consensus decision-making methods, as well as their practical applications. Intended for engineers, technicians, and researchers in the fields of computer linguistics, operations research, information science, management science and engineering, it also serves as a textbook for postgraduate and senior undergraduate university students.

This book presents intelligent data analysis as a tool to fight against COVID-19 pandemic. The intelligent data analysis includes machine learning, natural language processing, and computer vision applications to teach computers to use big data-based models for pattern recognition, explanation, and prediction. These functions are discussed in detail in the book to recognize (diagnose), predict, and explain (treat) COVID-19 infections, and help manage socio-economic impacts. It also discusses primary warnings and alerts; tracking and prediction; data dashboards; diagnosis and prognosis; treatments and cures; and social control by the use of intelligent data analysis. It provides analysis reports, solutions using real-time data, and solution through web applications details.

This book presents high-quality research papers presented at the International Conference on Soft Computing for Intelligent Systems (SCIS 2020), held during 18-20 December 2020 at University Institute of Engineering and Technology, Kurukshetra University, Kurukshetra, Haryana, India. The book encompasses all branches of artificial intelligence, computational sciences and machine learning which is based on computation at some level such as AI-based Internet of things, sensor networks, robotics, intelligent diabetic retinopathy, intelligent cancer genes analysis using computer vision, evolutionary algorithms, fuzzy systems, medical automatic identification intelligence system and applications in agriculture, health care, smart grid and instrumentation systems. The book is helpful for educators, researchers and developers working in the area of recent advances and upcoming technologies utilizing computational sciences in signal processing, imaging, computing, instrumentation, artificial intelligence and their applications.

This book explores the latest research trends in intelligent systems and smart applications. It presents high-quality empirical and review studies focusing on various topics, including information systems and software engineering, knowledge management, technology in education, emerging technologies, and social networks. It provides insights into the theoretical and practical aspects of intelligent systems and smart applications.

This book addresses the design of compliant mechanisms, presenting readers with a good understanding of both the solid mechanics of flexible elements and their configuration design, based on a mechanism-equivalent approach in the framework of screw theory. The book begins with the theoretical background of screw theory, and systematically addresses both the compliance characteristics of flexible elements and their configuration design. The book then covers a broad range of compliant parallel mechanism design topics, from stiffness to constraint decomposition, from conceptual design to dimensional design, and from analysis to synthesis, as well as the large deformation problem; this is followed by both simulations and physical experiments, offering readers a solid foundation and useful tools. Given its scope and the results it presents, the book will certainly benefit and inform future research on the topic. It offers a valuable asset for researchers, developers, engineers and graduate students with an interest in compliant mechanisms, robotics and screw theory.

A Financial Times and Economist Book of the Year 'Wonderfully stimulating... will teach you to see around corners' - TIM HARFORD 'A paean to cognitive agility and the elasticity of the imagination' - ECOMOMIST 'Captivating... will transform the way you think' MARISSA KING, PROFESSOR AT YALE SCHOOL OF MANAGEMENT The power of mental models to make better decisions We're often told that humans make bad decisions and that more data is better. But this is backwards: people are good at decisions precisely because we use mental models and can envision new realities outside of data. Great outcomes don't depend so much on the final moment of choosing but on generating better alternatives to choose between. That's framing. It's a cognitive muscle we can strengthen to improve our lives, work and future -- to meet this historical moment. Framers shows how.

This book presents the proceedings of the 2nd International Conference on Networks and Advances in Computational Technologies (NetACT19) which took place on July 23-25, 2019 at Mar Baselios College of Engineering and Technology in Thiruvananthapuram, India. The conference was in association with Bowie State University, USA, Gannon University, USA and Malardalen University, Sweden. Papers presented were included in technical programs that were part of five parallel tracks, namely Computer Application, Image Processing, Network Security, Hardware & Network Systems and Machine Learning. The proceedings brings together experts from industry, governments and academia from around the world with vast experiences in design, engineering and research. Presents the proceedings of the 2nd International Conference on Networks and Advances in Computational Technologies (NetACT19); Includes research in Computer Application, Image Processing, Network Security, Hardware & Network Systems and Machine Learning; Provides perspectives from industry, academia and government.

This edited book designs the Cognitive Computing in Human Cognition to analyze to improve the efficiency of decision making by cognitive intelligence. The book is also intended to attract the audience who work in brain computing, deep learning, transportation, and solar cell energy. Due to this in the recent era, smart methods with human touch called as human cognition is adopted by many researchers in the field of information technology with the Cognitive Computing.

This book includes selected papers from the International Conference on Next Generation of Internet of Things (ICNGIoT 2021), organized by the Department of Computer Science and Engineering, School of Engineering, GIET University, Gunupur, Odisha, India, during 5-6 February 2021. The book covers topics such as IoT network design and architecture, IoT network virtualization, IoT sensors, privacy and security for IoT, SMART environment, social networks, data science and data analytics, cognitive intelligence and augmented intelligence, and case studies and applications.

Integrated Science: Science without Borders" is the first volume of the INTEGRATED SCIENCE Book series, aiming to publish the results of the most updated ideas and reviews in transdisciplinary fields and to highlight the integration of discrete disciplines, including formal sciences, physical-chemical sciences and engineering, biological sciences, medical sciences, and social sciences. This volume primarily focuses on the research involving the integration of two or more academic fields offering an innovative, borderless view, which is one of the main focuses of the Universal Scientific Education and Research Network (USERN). The whole world is suffering from complex problems; these are borderless problems; thus, a borderless solution could merely solve such complex issues. Transdisciplinarity is a domain, that researchers work jointly, using a shared conceptual framework, drawing together disciplinary-specific theories, concepts, and approaches to address common problems. Lack of confidence, lack of expertise, complexities of healthcare, the confusing nature of healthcare environments, and lack of organization and standardization are the obstacles of successful scientific communication. Consequently, this book provides an overview of the essential elements of transdisciplinary studies and integrated science. The unique aspect of this book -privileging it from other books- is covering all aspects of science as harmonies of a single symphony.