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Artificial Intelligence: Its Philosophy and Neural Context (Routledge Library Editions: Artificial Intelligence)
by F. H. GeorgeOriginally published in 1986, in order to probe, dispute and analyse the role of artificial intelligence in cybernetic thought and information science, the author pursues this topic within its philosophical, behavioral and neurophysiological contexts, while drawing attention to cognitive issues. By elucidating the problems and potential associated with knowledge-based systems, the book emphasized the need to examine artificial intelligence in its own right.
Artificial Intelligence (Forensic Science in Focus)
by Zeno Geradts Katrin FrankeARTIFICIAL INTELLIGENCE (AI) IN FORENSIC SCIENCES Foundational text for teaching and learning within the field of Artificial Intelligence (AI) as it applies to forensic science Artificial Intelligence (AI) in Forensic Sciences presents an overview of the state-of-the-art applications of Artificial Intelligence within Forensic Science, covering issues with validation and new crimes that use AI; issues with triage, preselection, identification, argumentation and explain ability; demonstrating uses of AI in forensic science; and providing discussions on bias when using AI. The text discusses the challenges for the legal presentation of AI data and interpretation and offers solutions to this problem while addressing broader practical and emerging issues in a growing area of interest in forensics. It builds on key developing areas of focus in academic and government research, providing an authoritative and well-researched perspective. Compiled by two highly qualified editors with significant experience in the field, and part of the Wiley — AAFS series ‘Forensic Science in Focus’, Artificial Intelligence (AI) in Forensic Sciences includes information on: Cyber IoT, fundamentals on AI in forensic science, speaker and facial comparison, and deepfake detection Digital-based evidence creation, 3D and AI, interoperability of standards, and forensic audio and speech analysis Text analysis, video and multimedia analytics, reliability, privacy, network forensics, intelligence operations, argumentation support in court, and case applications Identification of genetic markers, current state and federal legislation with regards to AI, and forensics and fingerprint analysis Providing comprehensive coverage of the subject, Artificial Intelligence (AI) in Forensic Sciences is an essential advanced text for final year undergraduates and master’s students in forensic science, as well as universities teaching forensics (police, IT security, digital science and engineering), forensic product vendors and governmental and cyber security agencies.
Artificial Intelligence: A Driver of Inclusive Development and Shared Prosperity for the Global South
by Arthur G.O. MutambaraThis book presents contextualised and detailed research on Artificial Intelligence (AI) and the Global South. It examines the key challenges of these emerging and least industrialised countries while proffering holistic and comprehensive solutions. The book then explains how AI, as part of these broad interventions, can drive Global South economies to achieve inclusive development and shared prosperity. The book outlines how countries can swiftly prepare to adopt and develop AI across all sectors. It presents novel national, regional, and continental AI adoption, development, and implementation frameworks.Features: Broad non-AI interventions and prescriptions to address Global South challenges A comprehensive but accessible introduction to AI concepts, technology, infrastructure, systems, and innovations such as AlphaFold, ChatGPT-4, and DeepSeek-R1 An overview of AI-related technologies such as quantum computing, battery energy storage systems, 3D printing, nanotechnology, IoT, and blockchain How to prepare emerging economies to unlock the benefits of AI while mitigating the risks Discussion of specific AI applications in 11 critical Global South sectors Details of 11 sector case studies of AI adoption in the Global South and Global North Ten country case studies: Sharing emergent AI experiences in the Global South AI adoption framework: vision, strategy, policy, governance, legislation/regulation, and implementation matrix A framework for democratising and decolonising AI The value proposition for AI research, development, and ownership in the Global South A case for the participation of the Global South in the AI semiconductor industry This book is aimed at policymakers, business leaders, graduate students, academics, researchers, strategic thinkers, and world leaders seeking to understand and leverage the transformative role of AI-based systems in achieving inclusive development, economic transformation, and shared prosperity.
Artificial Intelligence (Studies in Systems, Decision and Control #517)
by Reem Khamis Hamdan Amina BuallayThe impact of artificial intelligence (AI) on business and society has been significant, with the incorporation of AI technologies such as robots, facial recognition, algorithms, and natural language processing into business leading to both corporate benefits and potential challenges for stakeholders. The question of how to engage in responsible business practices in the era of AI is an important one, and there is a need for more research on the relationship between AI and corporate social responsibility (CSR). As AI becomes more prevalent, there is a growing focus on the ethical implications of AI and the potential for AI to perpetuate biases or to displace human workers. CSR initiatives can include considerations of ethical AI in the development and use of AI systems. AI has the potential to solve many global challenges and improve people's lives, but it can also have negative consequences if not developed and used responsibly. CSR initiatives can focus on the social impact of AI,including efforts to ensure that the benefits of AI are distributed fairly and that AI is used for the common good. CSR initiatives often involve engaging with stakeholders, including employees, customers, and communities, to understand their needs and concerns and to ensure that their interests are taken into account. This can include engaging with stakeholders about the use of AI in the organization and its potential impactsThe adoption of AI in business is changing many aspects of doing business in a socially responsible manner, and there is a need to examine the potential unethical behaviors and novel ways of engaging in CSR that may arise. This book aims to focus on AI and CSR, and to advance our understanding of the role of AI in organizations and the literature on CSR by assembling high-quality papers with a strong connection between theory and practice.
Artificial Intelligence: Second International Conference, SLAAI-ICAI 2018, Moratuwa, Sri Lanka, December 20, 2018, Revised Selected Papers (Communications in Computer and Information Science #890)
by Jude Hemanth Thushari Silva Asoka KarunanandaThis book constitutes the refereed proceedings of the Second International Conference, SLAAI-ICAI 2018, held in Moratuwa, Sri Lanka, in December 2018.The 32 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in the following topical sections: intelligence systems; neural networks; game theory; ontology engineering; natural language processing; agent based system; signal and image processing.
Artificial Intelligence: What Everyone Needs to Know
by Jerry KaplanOver the coming decades, Artificial Intelligence will profoundly impact the way we live, work, wage war, play, seek a mate, educate our young, and care for our elderly. It is likely to greatly increase our aggregate wealth, but it will also upend our labor markets, reshuffle our social order, and strain our private and public institutions. Eventually it may alter how we see our place in the universe, as machines pursue goals independent of their creators and outperform us in domains previously believed to be the sole dominion of humans. Whether we regard them as conscious or unwitting, revere them as a new form of life or dismiss them as mere clever appliances, is beside the point. They are likely to play an increasingly critical and intimate role in many aspects of our lives. The emergence of systems capable of independent reasoning and action raises serious questions about just whose interests they are permitted to serve, and what limits our society should place on their creation and use. Deep ethical questions that have bedeviled philosophers for ages will suddenly arrive on the steps of our courthouses. Can a machine be held accountable for its actions? Should intelligent systems enjoy independent rights and responsibilities, or are they simple property? Who should be held responsible when a self-driving car kills a pedestrian? Can your personal robot hold your place in line, or be compelled to testify against you? If it turns out to be possible to upload your mind into a machine, is that still you? The answers may surprise you.
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.