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Artificial Intelligence in Sport Performance Analysis
by Duarte Araújo Micael S Couceiro Ludovic Seifert Hugo Sarmento Keith DavidsTo understand the dynamic patterns of behaviours and interactions between athletes that characterize successful performance in different sports is an important challenge for all sport practitioners. This book guides the reader in understanding how an ecological dynamics framework for use of artificial intelligence (AI) can be implemented to interpret sport performance and the design of practice contexts. By examining how AI methodologies are utilized in team games, such as football, as well as in individual sports, such as golf and climbing, this book provides a better understanding of the kinematic and physiological indicators that might better capture athletic performance by looking at the current state-of-the-art AI approaches. Artificial Intelligence in Sport Performance Analysis provides an all-encompassing perspective in an innovative approach that signals practical applications for both academics and practitioners in the fields of coaching, sports analysis, and sport science, as well as related subjects such as engineering, computer and data science, and statistics.
Artificial Intelligence in Sport Performance Analysis
by Duarte Araújo Micael S Couceiro Ludovic Seifert Hugo Sarmento Keith DavidsTo understand the dynamic patterns of behaviours and interactions between athletes that characterize successful performance in different sports is an important challenge for all sport practitioners. This book guides the reader in understanding how an ecological dynamics framework for use of artificial intelligence (AI) can be implemented to interpret sport performance and the design of practice contexts. By examining how AI methodologies are utilized in team games, such as football, as well as in individual sports, such as golf and climbing, this book provides a better understanding of the kinematic and physiological indicators that might better capture athletic performance by looking at the current state-of-the-art AI approaches. Artificial Intelligence in Sport Performance Analysis provides an all-encompassing perspective in an innovative approach that signals practical applications for both academics and practitioners in the fields of coaching, sports analysis, and sport science, as well as related subjects such as engineering, computer and data science, and statistics.
Artificial Intelligence. An International Perspective: An International Perspective (Lecture Notes in Computer Science #5640)
by Max BramerArtificial Intelligence (AI) is a rapidly growing inter-disciplinary field with a long and distinguished history that involves many countries and considerably pre-dates the development of computers. It can be traced back at least as far as Ancient Greece and has evolved over time to become a major subfield of computer science in general. This state-of-the-art survey not only serves as a "position paper" on the field from the viewpoint of expert members of the IFIP Technical Committee 12, its Working Groups and their colleagues, but also presents overviews of current work in different countries. The chapters describe important relatively new or emerging areas of work in which the authors are personally involved, including text and hypertext categorization; autonomous systems; affective intelligence; AI in electronic healthcare systems; artifact-mediated society and social intelligence design; multilingual knowledge management; agents, intelligence and tools; intelligent user profiling; and supply chain business intelligence. They provide an interesting international perspective on where this significant field is going at the end of the first decade of the twenty-first century.
Artificial Intelligence Logic and Applications: The 2nd International Conference, AILA 2022, Shanghai, China, August 26–28, 2022, Proceedings (Communications in Computer and Information Science #1657)
by Songmao Zhang Yixiang ChenThis book constitutes refereed proceedings of the 2nd International Conference on Artificial Intelligence Logic and Applications 2022 held in Shanghai, China from August 26–28, 2022.The 20 full papers presented in this volume were carefully reviewed and selected from a total of 27 submissions. The papers in the volume are organised according to the following topical headings: program logic; fuzzy logic; applications; author index.
Artificial Intelligence Logic and Applications: The 3rd International Conference, AILA 2023, Changchun, China, August 5–6, 2023, Proceedings (Communications in Computer and Information Science #1917)
by Songmao Zhang Yonggang ZhangThis book constitutes the proceedings of the Third International Conference, AILA 2023, held in Changchun, China, during August 5–6, 2023. The 26 full papers and the 10 short papers included in this volume were carefully reviewed and selected from 56 submissions. This volume aims to provide novel ideas, original research achievements, and practical experiences in a broad range of artificial intelligence logic and applications.
Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities: Designing for Sustainability (Springer Optimization and Its Applications #186)
by Panos M. Pardalos Stamatina Th. Rassia Arsenios TsokasThis volume offers a wealth of interdisciplinary approaches to artificial intelligence, machine learning and optimization tools, which contribute to the optimization of urban features towards forming smart, sustainable, and livable future cities.Special features include:New research on the design of city elements and smart systems with respect to new technologies and scientific thinkingDiscussions on the theoretical background that lead to smart cities for the futureNew technologies and principles of research that can promote ideas of artificial intelligence and machine learning in optimized urban environmentsThe book engages students and researchers in the subjects of artificial intelligence, machine learning, and optimization tools in smart sustainable cities as eminent international experts contribute their research results and thinking in its chapters. Overall, its audience can benefit from a variety of disciplines including, architecture, engineering, physics, mathematics, computer science, and related fields.
Artificial Intelligence Methods in the Environmental Sciences
by Sue Ellen Haupt Antonello Pasini Caren MarzbanHow can environmental scientists and engineers use the increasing amount of available data to enhance our understanding of planet Earth, its systems and processes? This book describes various potential approaches based on artificial intelligence (AI) techniques, including neural networks, decision trees, genetic algorithms and fuzzy logic. Part I contains a series of tutorials describing the methods and the important considerations in applying them. In Part II, many practical examples illustrate the power of these techniques on actual environmental problems. International experts bring to life ways to apply AI to problems in the environmental sciences. While one culture entwines ideas with a thread, another links them with a red line. Thus, a “red thread“ ties the book together, weaving a tapestry that pictures the ‘natural’ data-driven AI methods in the light of the more traditional modeling techniques, and demonstrating the power of these data-based methods.
Artificial Intelligence over Infrared Images for Medical Applications: Second MICCAI Workshop, AIIIMA 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 2, 2023, Proceedings (Lecture Notes in Computer Science #14298)
by Siva Teja Kakileti Geetha Manjunath Robert G. Schwartz Alejandro F. FrangiThis book constitutes the refereed proceedings of the Second Workshop on Artificial Intelligence over Infrared Images for Medical Applications, AIIIMA 2023 held in conjunction with MICCAI 2023, held in Vancouver, BC, Canada, on October 2, 2023. The 10 full papers presented in this book were carefully peer reviewed and selected from 15 submissions. The second workshop on AIIIMA, similarily to the first, aimes to create a forum to discuss the specific sub-topic of AI over Infrared Images for Medical Applications at MICCAI and promote this novel area of research, that has the potential to hugely impact our society, among the research community.
Artificial Intelligence Techniques for Rational Decision Making (Advanced Information and Knowledge Processing)
by Tshilidzi MarwalaDevelops insights into solving complex problems in engineering, biomedical sciences, social science and economics based on artificial intelligence. Some of the problems studied are in interstate conflict, credit scoring, breast cancer diagnosis, condition monitoring, wine testing, image processing and optical character recognition. The author discusses and applies the concept of flexibly-bounded rationality which prescribes that the bounds in Nobel Laureate Herbert Simon’s bounded rationality theory are flexible due to advanced signal processing techniques, Moore’s Law and artificial intelligence.Artificial Intelligence Techniques for Rational Decision Making examines and defines the concepts of causal and correlation machines and applies the transmission theory of causality as a defining factor that distinguishes causality from correlation. It develops the theory of rational counterfactuals which are defined as counterfactuals that are intended to maximize the attainment of a particular goal within the context of a bounded rational decision making process. Furthermore, it studies four methods for dealing with irrelevant information in decision making:Theory of the marginalization of irrelevant information Principal component analysis Independent component analysisAutomatic relevance determination methodIn addition it studies the concept of group decision making and various ways of effecting group decision making within the context of artificial intelligence.Rich in methods of artificial intelligence including rough sets, neural networks, support vector machines, genetic algorithms, particle swarm optimization, simulated annealing, incremental learning and fuzzy networks, this book will be welcomed by researchers and students working in these areas.
Artificial Intelligence Theory, Models, and Applications
by P. KalirajThis book examines the fundamentals and technologies of Artificial Intelligence (AI) and describes their tools, challenges, and issues. It also explains relevant theory as well as industrial applications in various domains, such as healthcare, economics, education, product development, agriculture, human resource management, environmental management, and marketing. The book is a boon to students, software developers, teachers, members of boards of studies, and researchers who need a reference resource on artificial intelligence and its applications and is primarily intended for use in courses offered by higher education institutions that strive to equip their graduates with Industry 4.0 skills. FEATURES: Gender disparity in the enterprises involved in the development of AI-based software development as well as solutions to eradicate such gender bias in the AI world A general framework for AI in environmental management, smart farming, e-waste management, and smart energy optimization The potential and application of AI in medical imaging as well as the challenges of AI in precision medicine AI’s role in the diagnosis of various diseases, such as cancer and diabetes The role of machine learning models in product development and statistically monitoring product quality Machine learning to make robust and effective economic policy decisions Machine learning and data mining approaches to provide better video indexing mechanisms resulting in better searchable results ABOUT THE EDITORS: Prof. Dr. P. Kaliraj is Vice Chancellor at Bharathiar University, Coimbatore, India. Prof. Dr. T. Devi is Professor and Head of the Department of Computer Applications, Bharathiar University, Coimbatore, India.
Artificial Intelligence Theory, Models, and Applications
by P. Kaliraj T. DeviThis book examines the fundamentals and technologies of Artificial Intelligence (AI) and describes their tools, challenges, and issues. It also explains relevant theory as well as industrial applications in various domains, such as healthcare, economics, education, product development, agriculture, human resource management, environmental management, and marketing. The book is a boon to students, software developers, teachers, members of boards of studies, and researchers who need a reference resource on artificial intelligence and its applications and is primarily intended for use in courses offered by higher education institutions that strive to equip their graduates with Industry 4.0 skills. FEATURES: Gender disparity in the enterprises involved in the development of AI-based software development as well as solutions to eradicate such gender bias in the AI world A general framework for AI in environmental management, smart farming, e-waste management, and smart energy optimization The potential and application of AI in medical imaging as well as the challenges of AI in precision medicine AI’s role in the diagnosis of various diseases, such as cancer and diabetes The role of machine learning models in product development and statistically monitoring product quality Machine learning to make robust and effective economic policy decisions Machine learning and data mining approaches to provide better video indexing mechanisms resulting in better searchable results ABOUT THE EDITORS: Prof. Dr. P. Kaliraj is Vice Chancellor at Bharathiar University, Coimbatore, India. Prof. Dr. T. Devi is Professor and Head of the Department of Computer Applications, Bharathiar University, Coimbatore, India.
Artificial Intelligence Tools and Applications in Embedded and Mobile Systems: Selected Papers from the First International Conference on Embedded and Mobile Systems (ICTA-EMOS), 24-25 November 2022, Arusha, Tanzania (Progress in IS)
by Jorge Marx Gómez Anael Elikana Sam Devotha Godfrey NyamboThe emergence of Artificial Intelligence (AI) has had a tremendous impact on embedded and mobile systems. This book presents a diverse collection of papers that showcase cutting-edge research and practical applications of AI in this field. The peer-reviewed research articles stem from the First International Conference on Embedded and Mobile Systems (ICTA-EMOS), which was held on November 24th – 25th, 2022, in Arusha, Tanzania, East Africa. They demonstrate the breadth and depth of AI’s impact across various domains, exploring topics such as healthcare advances, transportation optimization, sustainable solutions, and business and process optimization.
Artificial Intelligence Versus Natural Intelligence
by Giacomo Mauro D'Ariano Roger Penrose Emanuele Severino Fabio Scardigli Ines Testoni Giuseppe Vitiello Federico FagginThis book centers around a dialogue between Roger Penrose and Emanuele Severino about one of most intriguing topics of our times, the comparison of artificial intelligence and natural intelligence, as well as its extension to the notions of human and machine consciousness.Additional insightful essays by Mauro D'Ariano, Federico Faggin, Ines Testoni, Giuseppe Vitiello and an introduction of Fabio Scardigli complete the book and illuminate different aspects of the debate. Although from completely different points of view, all the authors seem to converge on the idea that it is almost impossible to have real "intelligence" without a form of "consciousness". In fact, consciousness, often conceived as an enigmatic "mirror" of reality (but is it really a mirror?), is a phenomenon under intense investigation by science and technology, particularly in recent decades. Where does this phenomenon originate from (in humans, and perhaps also in animals)? Is it reproducible on some "device"? Do we have a theory of consciousness today? Will we arrive to build thinking or conscious machines, as machine learning, or cognitive computing, seem to promise? These questions and other related issues are discussed in the pages of this work, which provides stimulating reading to both specialists and general readers.The Chapter "Hard Problem and Free Will: An Information-Theoretical Approach" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Artificial Intelligence with Uncertainty
by Deyi Li Yi DuThis book develops a framework that shows how uncertainty in Artificial Intelligence (AI) expands and generalizes traditional AI. It explores the uncertainties of knowledge and intelligence. The authors focus on the importance of natural language – the carrier of knowledge and intelligence, and introduce efficient physical methods for data mining amd control. In this new edition, we have more in-depth description of the models and methods, of which the mathematical properties are proved strictly which make these theories and methods more complete. The authors also highlight their latest research results.
Artificial Intelligent Approaches in Petroleum Geosciences
by Constantin CranganuThis book presents cutting-edge approaches to solving practical problems faced by professionals in the petroleum industry and geosciences. With various state-of-the-art working examples from experienced academics, the book offers an exposure to the latest developments in intelligent methods for oil and gas research, exploration, and production. This second edition is updated with new chapters on machine learning approaches, data-driven modelling techniques, and neural networks. The book delves into machine learning approaches, including evolutionary algorithms, swarm intelligence, fuzzy logic, deep artificial neural networks, KNN, decision tree, random forest, XGBoost, and LightGBM. it also analyzes the strengths and weaknesses of each method and emphasizes essential parameters like robustness, accuracy, speed of convergence, computer time, overlearning, and normalization. Integration, data handling, risk management, and uncertainty management are all crucial issues in petroleum geosciences. The complexities of these problems require a multidisciplinary approach that fuses petroleum engineering, geology, geophysics, and geochemistry. Essentially, this book presents an approach for integrating various disciplines such as data fusion, risk reduction, and uncertainty management. Whether you are a professional or a student, you can greatly benefit from the latest advancements in intelligent methods applied to oil and gas research. This comprehensive and updated book presents cutting-edge approaches and real-world examples that can help you in solving the intricate challenges of the petroleum industry and geosciences.
Artificial Intelligent Approaches in Petroleum Geosciences
by Constantin Cranganu Henri Luchian Mihaela Elena BreabanThis book presents several intelligent approaches for tackling and solving challenging practical problems facing those in the petroleum geosciences and petroleum industry. Written by experienced academics, this book offers state-of-the-art working examples and provides the reader with exposure to the latest developments in the field of intelligent methods applied to oil and gas research, exploration and production. It also analyzes the strengths and weaknesses of each method presented using benchmarking, whilst also emphasizing essential parameters such as robustness, accuracy, speed of convergence, computer time, overlearning and the role of normalization. The intelligent approaches presented include artificial neural networks, fuzzy logic, active learning method, genetic algorithms and support vector machines, amongst others. Integration, handling data of immense size and uncertainty, and dealing with risk management are among crucial issues in petroleum geosciences. The problems we have to solve in this domain are becoming too complex to rely on a single discipline for effective solutions and the costs associated with poor predictions (e.g. dry holes) increase. Therefore, there is a need to establish a new approach aimed at proper integration of disciplines (such as petroleum engineering, geology, geophysics and geochemistry), data fusion, risk reduction and uncertainty management. These intelligent techniques can be used for uncertainty analysis, risk assessment, data fusion and mining, data analysis and interpretation, and knowledge discovery, from diverse data such as 3-D seismic, geological data, well logging, and production data. This book is intended for petroleum scientists, data miners, data scientists and professionals and post-graduate students involved in petroleum industry.
Artificial Life and Evolutionary Computation: 13th Italian Workshop, WIVACE 2018, Parma, Italy, September 10–12, 2018, Revised Selected Papers (Communications in Computer and Information Science #900)
by Stefano Cagnoni Marco Villani Andrea Roli Monica Mordonini Riccardo PecoriThis book constitutes the revised selected papers of the 13th Italian Workshop on Artificial Life and Evolutionary Computation, WIVACE 2018, held in Parma, Italy, in September 2018. The 12 full papers presented were thoroughly reviewed and selected from 30 submissions. They cover the following topics: Boolean networks and complex systems; economic, societal and technological applications; chemical, biological and medical applications. The chapter “Unveiling Latent Relations in the Photonics Techno-Economic Complex System” is open access under a CC BY 4.0 license at link.springer.com.
Artificial Life and Evolutionary Computation: 12th Italian Workshop, WIVACE 2017, Venice, Italy, September 19-21, 2017, Revised Selected Papers (Communications in Computer and Information Science #830)
by Marcello Pelillo Irene Poli Andrea Roli Roberto Serra Debora Slanzi Marco VillaniThis book constitutes the revised selected papers of the 12th Italian Workshop on Advances in Artificial Life, Evolutionary Computation, WIVACE 2017, held in Venice, Italy, in September 2017.The 23 full papers presented were thoroughly reviewed and selected from 33 submissions. They cover the following topics: physical-chemical phenomena; biological systems; economy and society; complexity; optimization.
Artificial Life and Evolutionary Computation: 17th Italian Workshop, WIVACE 2023, Venice, Italy, September 6–8, 2023, Revised Selected Papers (Communications in Computer and Information Science #1977)
by Marco Villani Stefano Cagnoni Roberto SerraThis book constitutes the refereed post proceedings of the 17th Italian Workshop on Artificial Life and Evolutionary Computation, WIVACE 2023, held in Venice, Italy, during September 6–8, 2023.The 30 full papers included in this book were carefully reviewed and selected from 55 submissions. They were organized in topical sections as follows: Algorithms for complex systems, Biologically inspired models, Complex chemical systems, Adaptation and swarms, Learning, Medicine and Social systems.
Artificial Markets Modeling: Methods and Applications (Lecture Notes in Economics and Mathematical Systems #599)
by Andrea ConsiglioThis volume features contributions to agent-based computational modeling from the social sciences and computer sciences. It presents applications of methodologies and tools, focusing on the uses, requirements, and constraints of agent-based models used by social scientists. Topics include agent-based macroeconomics, the emergence of norms and conventions, the dynamics of social and economic networks, and behavioral models in financial markets.
Artificial Mathematical Intelligence: Cognitive, (Meta)mathematical, Physical and Philosophical Foundations
by Danny A. Gómez RamírezThis volume discusses the theoretical foundations of a new inter- and intra-disciplinary meta-research discipline, which can be succinctly called cognitive metamathematics, with the ultimate goal of achieving a global instance of concrete Artificial Mathematical Intelligence (AMI). In other words, AMI looks for the construction of an (ideal) global artificial agent being able to (co-)solve interactively formal problems with a conceptual mathematical description in a human-style way. It first gives formal guidelines from the philosophical, logical, meta-mathematical, cognitive, and computational points of view supporting the formal existence of such a global AMI framework, examining how much of current mathematics can be completely generated by an interactive computer program and how close we are to constructing a machine that would be able to simulate the way a modern working mathematician handles solvable mathematical conjectures from a conceptual point of view. The thesis that it is possible to meta-model the intellectual job of a working mathematician is heuristically supported by the computational theory of mind, which posits that the mind is in fact a computational system, and by the meta-fact that genuine mathematical proofs are, in principle, algorithmically verifiable, at least theoretically. The introduction to this volume provides then the grounding multifaceted principles of cognitive metamathematics, and, at the same time gives an overview of some of the most outstanding results in this direction, keeping in mind that the main focus is human-style proofs, and not simply formal verification. The first part of the book presents the new cognitive foundations of mathematics’ program dealing with the construction of formal refinements of seminal (meta-)mathematical notions and facts. The second develops positions and formalizations of a global taxonomy of classic and new cognitive abilities, and computational tools allowing for calculation of formal conceptual blends are described. In particular, a new cognitive characterization of the Church-Turing Thesis is presented. In the last part, classic and new results concerning the co-generation of a vast amount of old and new mathematical concepts and the key parts of several standard proofs in Hilbert-style deductive systems are shown as well, filling explicitly a well-known gap in the mechanization of mathematics concerning artificial conceptual generation.
Artificial Neural Nets and Genetic Algorithms: Proceedings of the International Conference in Innsbruck, Austria, 1993
by Rudolf F. Albrecht Colin R. Reeves Nigel C. SteeleArtificial neural networks and genetic algorithms both are areas of research which have their origins in mathematical models constructed in order to gain understanding of important natural processes. By focussing on the process models rather than the processes themselves, significant new computational techniques have evolved which have found application in a large number of diverse fields. This diversity is reflected in the topics which are the subjects of contributions to this volume. There are contributions reporting theoretical developments in the design of neural networks, and in the management of their learning. In a number of contributions, applications to speech recognition tasks, control of industrial processes as well as to credit scoring, and so on, are reflected. Regarding genetic algorithms, several methodological papers consider how genetic algorithms can be improved using an experimental approach, as well as by hybridizing with other useful techniques such as tabu search. The closely related area of classifier systems also receives a significant amount of coverage, aiming at better ways for their implementation. Further, while there are many contributions which explore ways in which genetic algorithms can be applied to real problems, nearly all involve some understanding of the context in order to apply the genetic algorithm paradigm more successfully. That this can indeed be done is evidenced by the range of applications covered in this volume.
Artificial Neural Nets and Genetic Algorithms: Proceedings of the International Conference in Prague, Czech Republic, 2001
by Vera Kurkova Nigel C. Steele Roman Neruda Miroslav KarnyThe first ICANNGA conference, devoted to biologically inspired computational paradigms, Neural Net works and Genetic Algorithms, was held in Innsbruck, Austria, in 1993. The meeting attracted researchers from all over Europe and further afield, who decided that this particular blend of topics should form a theme for a series of biennial conferences. The second meeting, held in Ales, France, in 1995, carried on the tradition set in Innsbruck of a relaxed and stimulating environment for the. exchange of ideas. The series has continued in Norwich, UK, in 1997, and Portoroz, Slovenia, in 1999. The Institute of Computer Science, Czech Academy of Sciences, is pleased to host the fifth conference in Prague. We have chosen the Liechtenstein palace under the Prague Castle as the conference site to enhance the traditionally good atmosphere of the meeting. There is an inspirational genius loci of the historical center of the city, where four hundred years ago a fruitful combination of theoretical and empirical method, through the collaboration of Johannes Kepler and Tycho de Brahe, led to the discovery of the laws of planetary orbits.
Artificial Neural Networks: A Practical Course
by Ivan Nunes da Silva Danilo Hernane Spatti Rogerio Andrade Flauzino Luisa Helena Liboni Silas Franco dos Reis AlvesThis book provides comprehensive coverage of neural networks, their evolution, their structure, the problems they can solve, and their applications. The first half of the book looks at theoretical investigations on artificial neural networks and addresses the key architectures that are capable of implementation in various application scenarios. The second half is designed specifically for the production of solutions using artificial neural networks to solve practical problems arising from different areas of knowledge. It also describes the various implementation details that were taken into account to achieve the reported results. These aspects contribute to the maturation and improvement of experimental techniques to specify the neural network architecture that is most appropriate for a particular application scope. The book is appropriate for students in graduate and upper undergraduate courses in addition to researchers and professionals.
Artificial Neural Networks and Machine Learning – ICANN 2019: 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings (Lecture Notes in Computer Science #11731)
by Igor V. Tetko Věra Kůrková Pavel Karpov Fabian TheisThe proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions.