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Artificial Intelligence: Second CCF International Conference, ICAI 2019, Xuzhou, China, August 22-23, 2019, Proceedings (Communications in Computer and Information Science #1001)
by Kevin Knight Changshui Zhang Geoff Holmes Min-Ling ZhangThis book constitutes the refereed proceedings of the Second CCF International Conference on Artificial Intelligence, CCF-ICAI 2019, held in Xuzhou, China in August, 2019. The 23 papers presented were carefully reviewed and selected from 97 submissions. The papers are organized in topical sections on deep learning, image and video processing, NLP and recommender system, machine learning algorithms, and AI applications.
Artificial Intelligence: 19th International Conference, AIMSA 2024, Varna, Bulgaria, September 18–20, 2024, Proceedings (Lecture Notes in Computer Science #15462)
by Petia Koprinkova-Hristova Nikola KasabovThis book constitutes the refereed proceedings of the 19th International Conference on Artificial Intelligence: Methodology, Systems, and Applications, AIMSA 2024, held in Varna, Bulgaria, during September 18–20, 2024. The 18 revised full papers presented in this book were carefully reviewed and selected from 23 submissions. They cover a wide range of topics in AI and its applications: natural language processing, sentiment analyses, image processing, optimization, reinforcement learning, from deep ANNs to spike timing NNs, applications in economics, medicine and process control.
Artificial Intelligence: Technical and Societal Advancements (Artificial Intelligence for Sustainable Engineering and Management)
by Utku Kose Mustafa Umut DemirezenThis book provides an examination of cutting-edge research and developments in the field of artificial intelligence. It seeks to extend the view in both technical and societal evaluations to ensure a well-defined balance for societal outcomes. It explores hot topics such as generative artificial intelligence, artificial intelligence in law, education, and climate change.Artificial Intelligence: Technical and Societal Advancements seeks to bridge the gap between theory and practical applications of AI by giving readers insight into recent advancements. It offers readers a deep dive into the transformative power of AI for the present and future world. As artificial intelligence continues to revolutionize various sectors, the book discusses applications from healthcare to finance and from entertainment to industrial areas. It discusses the technical aspects of intelligent systems and the effects of these aspects on humans. To this point, this book considers technical advancements while discussing the societal pros and cons in terms of human-machine interaction in critical applications. The authors also stress the importance of deriving policies and predictions about how to make future intelligent systems compatible with humans through a necessary level of human management. Finally, this book provides the opinions and views of researchers and experts (from public/private sector) including educators, lawyers, policymakers, managers, and business-related representatives.The target readers of this book include academicians; researchers; experts; policymakers; educators; and B.S., M.S., and Ph.D. students in the context of target problem fields. It can be used accordingly as a reference source and even supportive material for artificial intelligence-oriented courses.
Artificial Intelligence: 19th Russian Conference, RCAI 2021, Taganrog, Russia, October 11–16, 2021, Proceedings (Lecture Notes in Computer Science #12948)
by Sergei M. Kovalev Sergei O. Kuznetsov Aleksandr I. PanovThis book constitutes the proceedings of the 19th Russian Conference on Artificial Intelligence, RCAI 2021, held in Moscow, Russia, in October 2021. The 19 full papers and 7 short papers presented in this volume were carefully reviewed and selected from 80 submissions. The conference deals with a wide range of topics, categorized into the following topical headings: cognitive research; data mining, machine learning, classification; knowledge engineering; multi-agent systems and robotics; natural language processing; fuzzy models and soft computer; intelligent systems; and tools for designing intelligent systems.
Artificial Intelligence: 16th Russian Conference, Rcai 2018, Moscow, Russia, September 24-26, 2018, Proceedings (Communications In Computer And Information Science #934)
by Sergei O. Kuznetsov Gennady S. Osipov Vadim L. StefanukThis book constitutes the proceedings of the 16th Russian Conference on Artificial Intelligence, RCAI 2018, Moscow, Russia, in September 2018. The 22 full papers presented along with 4 short papers in this volume were carefully reviewed and selected from 75 submissions. The conference deals with a wide range of topics, including data mining and knowledge discovery, text mining, reasoning, decision making, natural language processing, vision, intelligent robotics, multi-agent systems, machine learning, ontology engineering.
Artificial Intelligence: 17th Russian Conference, RCAI 2019, Ulyanovsk, Russia, October 21–25, 2019, Proceedings (Communications in Computer and Information Science #1093)
by Sergei O. Kuznetsov Aleksandr I. PanovThis book constitutes the proceedings of the 17th Russian Conference on Artificial Intelligence, RCAI 2019, held in Ulyanovsk, Russia, in October 2019. The 23 full papers presented along with 7 short papers in this volume were carefully reviewed and selected from 130 submissions. The conference deals with a wide range of topics, including multi-agent systems, intelligent robots and behaviour planning; automated reasoning and data mining; natural language processing and understanding of texts; fuzzy models and soft computing; intelligent systems and applications.
Artificial Intelligence: 18th Russian Conference, RCAI 2020, Moscow, Russia, October 10–16, 2020, Proceedings (Lecture Notes in Computer Science #12412)
by Sergei O. Kuznetsov Aleksandr I. Panov Konstantin S. YakovlevThis book constitutes the proceedings of the 18th Russian Conference on Artificial Intelligence, RCAI 2020, held in Moscow, Russia, in October 2020. The 27 full papers and 8 short papers presented in this volume were carefully reviewed and selected from 140 submissions. The conference deals with a wide range of topics, including data mining and knowledge discovery, text mining, reasoning, decisionmaking, natural language processing, vision, intelligent robotics, multi-agent systems,machine learning, AI in applied systems, and ontology engineering.
Artificial Intelligence: A Systems Approach from Architecture Principles to Deployment (MIT Lincoln Laboratory Series)
by David R. Martinez Bruke M. KifleThe first text to take a systems engineering approach to artificial intelligence (AI), from architecture principles to the development and deployment of AI capabilities.Most books on artificial intelligence (AI) focus on a single functional building block, such as machine learning or human-machine teaming. Artificial Intelligence takes a more holistic approach, addressing AI from the view of systems engineering. The book centers on the people-process-technology triad that is critical to successful development of AI products and services. Development starts with an AI design, based on the AI system architecture, and culminates with successful deployment of the AI capabilities. Directed toward AI developers and operational users, this accessibly written volume of the MIT Lincoln Laboratory Series can also serve as a text for undergraduate seniors and graduate-level students and as a reference book. Key features:In-depth look at modern computing technologies Systems engineering description and means to successfully undertake an AI product or service development through deploymentExisting methods for applying machine learning operations (MLOps)AI system architecture including a description of each of the AI pipeline building blocksChallenges and approaches to attend to responsible AI in practice Tools to develop a strategic roadmap and techniques to foster an innovative team environment Multiple use cases that stem from the authors&’ MIT classes, as well as from AI practitioners, AI project managers, early-career AI team leaders, technical executives, and entrepreneurs Exercises and Jupyter notebook examples
Artificial Intelligence: Building Smarter Machines
by Stephanie Sammartino McPhersonIn 2011 a computer named Watson outscored two human competitors on the TV quiz show Jeopardy! and snagged the million-dollar prize. Watson isn't the only machine keeping up with humans. The field of artificial intelligence (AI) is booming, with drones, robots, and computers handling tasks that once only humans could perform. Such advances raise challenging questions. Do Watson and other computers really think? Can machines acquire self-awareness? Is AI a promising or a dangerous technology? No machine, not even Watson, yet comes close to matching human intelligence, but many scientists believe it is only a matter of time before we reach this milestone. What will such a future look like?
Artificial Intelligence: A Guide for Thinking Humans (Pelican Bks.)
by Melanie MitchellNo recent scientific enterprise has proved as alluring, terrifying, and filled with extravagant promise and frustrating setbacks as artificial intelligence. The award-winning author Melanie Mitchell, a leading computer scientist, now reveals AI’s turbulent history and the recent spate of apparent successes, grand hopes, and emerging fears surrounding it.In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent—really—are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant models of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought underpinning recent achievements. She meets with fellow experts such as Douglas Hofstadter, the cognitive scientist and Pulitzer Prize–winning author of the modern classic Gödel, Escher, Bach, who explains why he is “terrified” about the future of AI. She explores the profound disconnect between the hype and the actual achievements in AI, providing a clear sense of what the field has accomplished and how much further it has to go. Interweaving stories about the science of AI and the people behind it, Artificial Intelligence brims with clear-sighted, captivating, and accessible accounts of the most interesting and provocative modern work in the field, flavored with Mitchell’s humor and personal observations. This frank, lively book is an indispensable guide to understanding today’s AI, its quest for “human-level” intelligence, and its impact on the future for us all.
Artificial Intelligence: With an Introduction to Machine Learning (Second Edition) (Chapman & Hall/CRC Artificial Intelligence and Robotics Series)
by Richard E. Neapolitan Xia JiangThe first edition of this popular textbook, Contemporary Artificial Intelligence, provided an accessible and student friendly introduction to AI. This fully revised and expanded update, Artificial Intelligence: With an Introduction to Machine Learning, Second Edition, retains the same accessibility and problem-solving approach, while providing new material and methods. The book is divided into five sections that focus on the most useful techniques that have emerged from AI. The first section of the book covers logic-based methods, while the second section focuses on probability-based methods. Emergent intelligence is featured in the third section and explores evolutionary computation and methods based on swarm intelligence. The newest section comes next and provides a detailed overview of neural networks and deep learning. The final section of the book focuses on natural language understanding. Suitable for undergraduate and beginning graduate students, this class-tested textbook provides students and other readers with key AI methods and algorithms for solving challenging problems involving systems that behave intelligently in specialized domains such as medical and software diagnostics, financial decision making, speech and text recognition, genetic analysis, and more.
Artificial Intelligence: A Modern Approach, Third Edition
by Peter Norvig Stuart J. RussellThis third edition of Artificial Intelligence: A Modern Approach offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. This textbook is useful for one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence.
Artificial Intelligence: 5th RAAI Summer School, Dolgoprudny, Russia, July 4–7, 2019, Tutorial Lectures (Lecture Notes in Computer Science #11866)
by Gennady S. Osipov Aleksandr I. Panov Konstantin S. YakovlevThis volume contains selected tutorial and young scientist school papers of the 5th RAAI Summer School on Artificial Intelligence, held in July 2019 at Institute of Physics and Technology (MIPT) campus in Dolgoprudny, a suburb of Moscow, Russia. The 11 chapters in this volume present papers focusing on various important aspects of Multiagent systems; Behavior planning; Natural language processing; Modeling of reasoning; and Machine learning and data analysis.
Artificial Intelligence: What Is Behind the Technology of the Future?
by Gerhard Paaß Dirk HeckerArtificial Intelligence (AI) is already present in our daily routines, and in the future, we will encounter it in almost every aspect of life – from analyzing X-rays for medical diagnosis, driving autonomous cars, maintaining complex machinery, to drafting essays on environmental problems and drawing imaginative pictures. The potentials of AI are enormous, while at the same time many myths, uncertainties and challenges circulate that need to be tackled. The English translation of the book “Künstliche Intelligenz – Was steckt hinter der Technologie der Zukunft?” originally published in German (Springer Vieweg, 2020), this book is addressed to the general public, from interested citizens to corporate executives who want to develop a better and deeper understanding of AI technologies and assess their consequences. Mathematical basics, terminology, and methods are explained in understandable language. Adaptations to different media such as images, text, and speech and the corresponding generative models are introduced. A concluding discussion of opportunities and challenges helps readers evaluate new developments, demystify them, and assess their relevance for the future.
Artificial Intelligence: From Medieval Robots to Neural Networks (Union Square & Co. Illustrated Histories)
by Clifford A. Pickover“This is an addictive stroll through the annals of artificial intelligence, highlighting almost 100 innovations developed between 1300 BCE and 2018” (Booklist).From medieval robots and Boolean algebra to facial recognition, artificial neural networks, and adversarial patches, this fascinating history takes readers on a lively tour through the world of artificial intelligence. Award–winning author Clifford A. Pickover (The Math Book, The Physics Book, Death & the Afterlife) explores the historic and current applications of AI in such diverse fields as computing, medicine, popular culture, mythology, and philosophy, and considers the enduring threat to humanity should AI grow out of control. Across 100 illustrated entries, Pickover provides an entertaining and informative look into when artificial intelligence began, how it developed, where it’s going, and what it means for the future of human-machine interaction.“An enjoyable diversion to read cover to cover, follow along common strands, or dip into for random bits.” —Booklist
Artificial Intelligence: From Medieval Robots to Neural Networks (Union Square & Co. Illustrated Histories)
by Clifford A. PickoverA History of the Future that's Happening Right NowArtificial Intelligence: An Illustrated History explores the historic origins and current applications of AI in such diverse fields as computing, medicine, popular culture, mythology, and philosophy. Through more than 100 entries, award-winning author Clifford A. Pickover, offers a granular, yet accessible, glimpse into the world of AI—from medieval robots and Boolean algebra to facial recognition, and artificial neural networks. First released in 2019, this updated paperback edition brings readers up to speed with coverage of technologies such as DALL-E and ChatGPT, and it explores the very real fear that AI will alter the course of humanity—forever.
Artificial Intelligence
by David L. Poole Alan K. MackworthConstraint-based reasoning is an important area of automated reasoning in artificial intelligence, with many applications. These include configuration and design problems, planning and scheduling, temporal and spatial reasoning, defeasible and causal reasoning, machine vision and language understanding, qualitative and diagnostic reasoning, and expert systems. Constraint-Based Reasoning presents current work in the field at several levels: theory, algorithms, languages, applications, and hardware. Constraint-based reasoning has connections to a wide variety of fields, including formal logic, graph theory, relational databases, combinatorial algorithms, operations research, neural networks, truth maintenance, and logic programming. The ideal of describing a problem domain in natural, declarative terms and then letting general deductive mechanisms synthesize individual solutions has to some extent been realized, and even embodied, in programming languages. Contents :- Introduction, E. C. Freuder, A. K. Mackworth. - The Logic of Constraint Satisfaction, A. K. Mackworth. - Partial Constraint Satisfaction, E. C. Freuder, R. J. Wallace. - Constraint Reasoning Based on Interval Arithmetic: The Tolerance Propagation Approach, E. Hyvonen. - Constraint Satisfaction Using Constraint Logic Programming, P. Van Hentenryck, H. Simonis, M. Dincbas. - Minimizing Conflicts: A Heuristic Repair Method for Constraint Satisfaction and Scheduling Problems, S. Minton, M. D. Johnston, A. B. Philips, and P. Laird. - Arc Consistency: Parallelism and Domain Dependence, P. R. Cooper, M. J. Swain. - Structure Identification in Relational Data, R. Dechter, J. Pearl. - Learning to Improve Constraint-Based Scheduling, M. Zweben, E. Davis, B. Daun, E. Drascher, M. Deale, M. Eskey. - Reasoning about Qualitative Temporal Information, P. van Beek. - A Geometric Constraint Engine, G. A. Kramer. - A Theory of Conflict Resolution in Planning, Q. Yang. A Bradford Book.
Artificial Intelligence: Applications and Innovations (Chapman & Hall/Distributed Computing and Intelligent Data Analytics Series)
by Rashmi Priyadarshini, R M Mehra, Amit Sehgal and Prabhu Jyot SinghArtificial Intelligence: Applications and Innovations is a book about the science of artificial intelligence (AI). AI is the study of the design of intelligent computational agents. This book provides a valuable resource for researchers, scientists, professionals, academicians and students dealing with the new challenges and advances in the areas of AI and innovations. This book also covers a wide range of applications of machine learning such as fire detection, structural health and pollution monitoring and control. Key Features Provides insight into prospective research and application areas related to industry and technology Discusses industry- based inputs on success stories of technology adoption Discusses technology applications from a research perspective in the field of AI Provides a hands- on approach and case studies for readers of the book to practice and assimilate learning This book is primarily aimed at graduates and post- graduates in computer science, information technology, civil engineering, electronics and electrical engineering and management.
Artificial Intelligence: Applications in Healthcare Delivery
by Sandeep ReddyThe rediscovery of the potential of artificial intelligence (AI) to improve healthcare delivery and patient outcomes has led to an increasing application of AI techniques such as deep learning, computer vision, natural language processing, and robotics in the healthcare domain. Many governments and health authorities have prioritized the application of AI in the delivery of healthcare. Also, technological giants and leading universities have established teams dedicated to the application of AI in medicine. These trends will mean an expanded role for AI in the provision of healthcare. Yet, there is an incomplete understanding of what AI is and its potential for use in healthcare. This book discusses the different types of AI applicable to healthcare and their application in medicine, population health, genomics, healthcare administration, and delivery. Readers, especially healthcare professionals and managers, will find the book useful to understand the different types of AI and how they are relevant to healthcare delivery. The book provides examples of AI being applied in medicine, population health, genomics, healthcare administration, and delivery and how they can commence applying AI in their health services. Researchers and technology professionals will also find the book useful to note current trends in the application of AI in healthcare and initiate their own projects to enable the application of AI in healthcare/medical domains.
Artificial Intelligence: 10 Things You Should Know (10 Things You Should Know)
by Professor Tim Rocktäschel"An excellent, extremely up-to-date overview of the most important technological revolution in human history." - Prof. Jeff Clune, University of British Columbia"If I were to recommend one book on AI, this would be it!" - Dr Edward Hughes, LSE & Google DeepMindExplore humanity's most transformative technology: artificial intelligence...In ten short and informative essays, Professor of AI at University College London, Tim Rocktäschel, reveals everything we need to know about artificial intelligence. From what the futures holds for AI and why it continues to improve with more data, to how superhuman AI is attainable and why we still have to fold our own laundry, discover all of this and much, much more!Artificial Intelligence: 10 Things You Should Know is an illuminating and engaging guide to the most important area of science and technology today.
Artificial Intelligence: 10 Things You Should Know (10 Things You Should Know)
by Professor Tim Rocktäschel"An excellent, extremely up-to-date overview of the most important technological revolution in human history." - Prof. Jeff Clune, University of British Columbia"If I were to recommend one book on AI, this would be it!" - Dr Edward Hughes, LSE & Google DeepMindExplore humanity's most transformative technology: artificial intelligence...In ten short and informative essays, Professor of AI at University College London, Tim Rocktäschel, reveals everything we need to know about artificial intelligence. From what the futures holds for AI and why it continues to improve with more data, to how superhuman AI is attainable and why we still have to fold our own laundry, discover all of this and much, much more!Artificial Intelligence: 10 Things You Should Know is an illuminating and engaging guide to the most important area of science and technology today.
Artificial Intelligence: 10 Things You Should Know (10 Things You Should Know)
by Professor Tim Rocktäschel"An excellent, extremely up-to-date overview of the most important technological revolution in human history." - Prof. Jeff Clune, University of British Columbia"If I were to recommend one book on AI, this would be it!" - Dr Edward Hughes, LSE & Google DeepMindExplore humanity's most transformative technology: artificial intelligence...In ten short and informative essays, Professor of AI at University College London, Tim Rocktäschel, reveals everything we need to know about artificial intelligence. From what the futures holds for AI and why it continues to improve with more data, to how superhuman AI is attainable and why we still have to fold our own laundry, discover all of this and much, much more!Artificial Intelligence: 10 Things You Should Know is an illuminating and engaging guide to the most important area of science and technology today.
Artificial Intelligence: A Modern Approach
by Stuart Russell Peter NorvigArtificial Intelligence: A Modern Approach (AIMA) is a university textbook on artificial intelligence, written by Stuart J. Russell and Peter Norvig. It was first published in 1995 and the fourth edition of the book was released 28 April 2020. It is used in over 1400 universities worldwide and has been called "the most popular artificial intelligence textbook in the world". It is considered the standard text in the field of artificial intelligence. The book is intended for an undergraduate audience but can also be used for graduate-level studies with the suggestion of adding some of the primary sources listed in the extensive bibliography.
Artificial Intelligence: Recent Trends and Applications (Artificial Intelligence (AI): Elementary to Advanced Practices)
by S. Kanimozhi Suguna, M. Dhivya, and Sara PaivaThis book aims to bring together leading academic scientists, researchers, and research scholars to exchange and share their experiences and research results on all aspects of Artificial Intelligence. The book provides a premier interdisciplinary platform to present practical challenges and adopted solutions. The book addresses the complete functional framework workflow in Artificial Intelligence technology. It explores the basic and high-level concepts and can serve as a manual for the industry for beginners and the more advanced. It covers intelligent and automated systems and its implications to the real-world, and offers data acquisition and case studies related to data-intensive technologies in AI-based applications. The book will be of interest to researchers, professionals, scientists, professors, students of computer science engineering, electronics and communications, as well as information technology.
Artificial Intelligence: First International Conference, ICAITA 2022, Mascara, Algeria, November 7–8, 2022, Revised Selected Papers (Communications in Computer and Information Science #1769)
by Mohammed Salem Juan Julián Merelo Patrick Siarry Rochdi Bachir Bouiadjra Mohamed Debakla Fatima DebbatThis volume constitutes selected papers presented at the First International Conference on Artificial Intelligence: Theories and Applications, ICAITA 2022, held in Mascara, Algeria, in November 2022. The 23 papers were thoroughly reviewed and selected from the 66 qualified submissions. They are organized in topical sections on artificial vision; and articial intelligence in big data and natural language processing.