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Author: David L. Poole
Publisher: Cambridge University Press
Published: 2017-09-25
Total Pages: 821
ISBN-13: 110719539X
DOWNLOAD EBOOKArtificial Intelligence presents a practical guide to AI, including agents, machine learning and problem-solving simple and complex domains.
Author: Siva Sankar Namani
Publisher: Archers & Elevators Publishing House
Published:
Total Pages: 111
ISBN-13: 8119385322
DOWNLOAD EBOOKAuthor: Andrew Lowe
Publisher: BCS, The Chartered Institute for IT
Published: 2020-08-24
Total Pages: 160
ISBN-13: 9781780175287
DOWNLOAD EBOOKIn line with the BCS AI Foundation and Essentials certificates, this book guides you through the world of AI. You will learn how AI is being utilised today, and how it is likely to be used in the future. You will explore robotics and machine learning within the context of AI, and discover how the challenges AI presents are being addressed.
Author: I. Tiddi
Publisher: IOS Press
Published: 2020-05-06
Total Pages: 314
ISBN-13: 1643680811
DOWNLOAD EBOOKThe latest advances in Artificial Intelligence and (deep) Machine Learning in particular revealed a major drawback of modern intelligent systems, namely the inability to explain their decisions in a way that humans can easily understand. While eXplainable AI rapidly became an active area of research in response to this need for improved understandability and trustworthiness, the field of Knowledge Representation and Reasoning (KRR) has on the other hand a long-standing tradition in managing information in a symbolic, human-understandable form. This book provides the first comprehensive collection of research contributions on the role of knowledge graphs for eXplainable AI (KG4XAI), and the papers included here present academic and industrial research focused on the theory, methods and implementations of AI systems that use structured knowledge to generate reliable explanations. Introductory material on knowledge graphs is included for those readers with only a minimal background in the field, as well as specific chapters devoted to advanced methods, applications and case-studies that use knowledge graphs as a part of knowledge-based, explainable systems (KBX-systems). The final chapters explore current challenges and future research directions in the area of knowledge graphs for eXplainable AI. The book not only provides a scholarly, state-of-the-art overview of research in this subject area, but also fosters the hybrid combination of symbolic and subsymbolic AI methods, and will be of interest to all those working in the field.
Author: Jeremy Watt
Publisher: Cambridge University Press
Published: 2020-01-09
Total Pages: 597
ISBN-13: 1108480721
DOWNLOAD EBOOKAn intuitive approach to machine learning covering key concepts, real-world applications, and practical Python coding exercises.
Author: G. M. P. O'Hare
Publisher: John Wiley & Sons
Published: 1996-04-05
Total Pages: 598
ISBN-13: 9780471006756
DOWNLOAD EBOOKDistributed Artificial Intelligence (DAI) is a dynamic area of research and this book is the first comprehensive, truly integrated exposition of the discipline presenting influential contributions from leaders in the field. Commences with a solid introduction to the theoretical and practical issues of DAI, followed by a discussion of the core research topics--communication, coordination, planning--and how they are related to each other. The third section describes a number of DAI testbeds, illustrating particular strategies commissioned to provide software environments for building and experimenting with DAI systems. The final segment contains contributions which consider DAI from different perspectives.
Author: Virginia Dignum
Publisher: Springer Nature
Published: 2019-11-04
Total Pages: 133
ISBN-13: 3030303713
DOWNLOAD EBOOKIn this book, the author examines the ethical implications of Artificial Intelligence systems as they integrate and replace traditional social structures in new sociocognitive-technological environments. She discusses issues related to the integrity of researchers, technologists, and manufacturers as they design, construct, use, and manage artificially intelligent systems; formalisms for reasoning about moral decisions as part of the behavior of artificial autonomous systems such as agents and robots; and design methodologies for social agents based on societal, moral, and legal values. Throughout the book the author discusses related work, conscious of both classical, philosophical treatments of ethical issues and the implications in modern, algorithmic systems, and she combines regular references and footnotes with suggestions for further reading. This short overview is suitable for undergraduate students, in both technical and non-technical courses, and for interested and concerned researchers, practitioners, and citizens.
Author: K.R. Chowdhary
Publisher: Springer Nature
Published: 2020-04-04
Total Pages: 730
ISBN-13: 8132239725
DOWNLOAD EBOOKFundamentals of Artificial Intelligence introduces the foundations of present day AI and provides coverage to recent developments in AI such as Constraint Satisfaction Problems, Adversarial Search and Game Theory, Statistical Learning Theory, Automated Planning, Intelligent Agents, Information Retrieval, Natural Language & Speech Processing, and Machine Vision. The book features a wealth of examples and illustrations, and practical approaches along with the theoretical concepts. It covers all major areas of AI in the domain of recent developments. The book is intended primarily for students who major in computer science at undergraduate and graduate level but will also be of interest as a foundation to researchers in the area of AI.
Author: Thomas D. Grant
Publisher: Springer Nature
Published: 2020-06-02
Total Pages: 163
ISBN-13: 3030435822
DOWNLOAD EBOOKThis open access book explores machine learning and its impact on how we make sense of the world. It does so by bringing together two ‘revolutions’ in a surprising analogy: the revolution of machine learning, which has placed computing on the path to artificial intelligence, and the revolution in thinking about the law that was spurred by Oliver Wendell Holmes Jr in the last two decades of the 19th century. Holmes reconceived law as prophecy based on experience, prefiguring the buzzwords of the machine learning age—prediction based on datasets. On the path to AI introduces readers to the key concepts of machine learning, discusses the potential applications and limitations of predictions generated by machines using data, and informs current debates amongst scholars, lawyers and policy makers on how it should be used and regulated wisely. Technologists will also find useful lessons learned from the last 120 years of legal grappling with accountability, explainability, and biased data.
Author: Louis J. Catania
Publisher: Academic Press
Published: 2020-11-25
Total Pages: 562
ISBN-13: 0323860052
DOWNLOAD EBOOKFoundational Handbook of Artificial Intelligence in Healthcare and Bioscience: A User Friendly Guide for IT Professionals, Healthcare Providers, Researchers, and Clinicians uses color-coded illustrations to explain AI from its basics to modern technologies. Other sections cover extensive, current literature research and citations regarding AI's role in the business and clinical aspects of health care. The book provides readers with a unique opportunity to appreciate AI technology in practical terms, understand its applications, and realize its profound influence on the clinical and business aspects of health care. Artificial Intelligence is a disruptive technology that is having a profound and growing influence on the business of health care as well as medical diagnosis, treatment, research and clinical delivery. The AI relationships in health care are complex, but understandable, especially when discussed and developed from their foundational elements through to their practical applications in health care. - Provides an illustrated, foundational guide and comprehensive descriptions of what Artificial Intelligence is and how it functions - Integrates a comprehensive discussion of AI applications in the business of health care - Presents in-depth clinical and AI-related discussions on diagnostic medicine, therapeutic medicine, and prevalent disease categories with an emphasis on immunology and genetics, the two categories most influenced by AI - Includes comprehensive coverage of a variety of AI treatment applications, including medical/pharmaceutical care, nursing care, stem cell therapies, robotics, and 10 common disease categories with AI applications
