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Book Artificial Intelligence Foundations and Applications

Download or read book Artificial Intelligence Foundations and Applications written by Siva Sankar Namani and published by Archers & Elevators Publishing House. This book was released on with total page 111 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Artificial Intelligence

    Book Details:
  • Author : David L. Poole
  • Publisher : Cambridge University Press
  • Release : 2017-09-25
  • ISBN : 110719539X
  • Pages : 821 pages

Download or read book Artificial Intelligence written by David L. Poole and published by Cambridge University Press. This book was released on 2017-09-25 with total page 821 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence presents a practical guide to AI, including agents, machine learning and problem-solving simple and complex domains.

Book Artificial Intelligence Foundations

    Book Details:
  • Author : Andrew Lowe
  • Publisher : BCS, The Chartered Institute for IT
  • Release : 2020-08-24
  • ISBN : 9781780175287
  • Pages : 160 pages

Download or read book Artificial Intelligence Foundations written by Andrew Lowe and published by BCS, The Chartered Institute for IT. This book was released on 2020-08-24 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: In 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.

Book Artificial Intelligence

Download or read book Artificial Intelligence written by Patrick Henry Winston and published by . This book was released on 1987 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Explainable AI  Foundations  Methodologies and Applications

Download or read book Explainable AI Foundations Methodologies and Applications written by Mayuri Mehta and published by Springer Nature. This book was released on 2022-10-19 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents an overview and several applications of explainable artificial intelligence (XAI). It covers different aspects related to explainable artificial intelligence, such as the need to make the AI models interpretable, how black box machine/deep learning models can be understood using various XAI methods, different evaluation metrics for XAI, human-centered explainable AI, and applications of explainable AI in health care, security surveillance, transportation, among other areas. The book is suitable for students and academics aiming to build up their background on explainable AI and can guide them in making machine/deep learning models more transparent. The book can be used as a reference book for teaching a graduate course on artificial intelligence, applied machine learning, or neural networks. Researchers working in the area of AI can use this book to discover the recent developments in XAI. Besides its use in academia, this book could be used by practitioners in AI industries, healthcare industries, medicine, autonomous vehicles, and security surveillance, who would like to develop AI techniques and applications with explanations.

Book Engineering Mathematics and Artificial Intelligence

Download or read book Engineering Mathematics and Artificial Intelligence written by Herb Kunze and published by CRC Press. This book was released on 2023-07-26 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explains the theory behind Machine Learning and highlights how Mathematics can be used in Artificial Intelligence Illustrates how to improve existing algorithms by using advanced mathematics and discusses how Machine Learning can support mathematical modeling Captures how to simulate data by means of artificial neural networks and offers cutting-edge Artificial Intelligence technologies Emphasizes the classification of algorithms, optimization methods, and statistical techniques Explores future integration between Machine Learning and complex mathematical techniques

Book Handbook of Research on Foundations and Applications of Intelligent Business Analytics

Download or read book Handbook of Research on Foundations and Applications of Intelligent Business Analytics written by Sun, Zhaohao and published by IGI Global. This book was released on 2022-03-11 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent business analytics is an emerging technology that has become a mainstream market adopted broadly across industries, organizations, and geographic regions. Intelligent business analytics is a current focus for research and development across academia and industries and must be examined and considered thoroughly so businesses can apply the technology appropriately. The Handbook of Research on Foundations and Applications of Intelligent Business Analytics examines the technologies and applications of intelligent business analytics and discusses the foundations of intelligent analytics such as intelligent mining, intelligent statistical modeling, and machine learning. Covering topics such as augmented analytics and artificial intelligence systems, this major reference work is ideal for scholars, engineers, professors, practitioners, researchers, industry professionals, academicians, and students.

Book Foundations of Distributed Artificial Intelligence

Download or read book Foundations of Distributed Artificial Intelligence written by G. M. P. O'Hare and published by John Wiley & Sons. This book was released on 1996-04-05 with total page 598 pages. Available in PDF, EPUB and Kindle. Book excerpt: Distributed 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.

Book Knowledge Graphs for eXplainable Artificial Intelligence  Foundations  Applications and Challenges

Download or read book Knowledge Graphs for eXplainable Artificial Intelligence Foundations Applications and Challenges written by I. Tiddi and published by IOS Press. This book was released on 2020-05-06 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 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.

Book Stochastic Local Search

Download or read book Stochastic Local Search written by Holger H. Hoos and published by Morgan Kaufmann. This book was released on 2005 with total page 678 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic local search (SLS) algorithms are among the most prominent and successful techniques for solving computationally difficult problems. Offering a systematic treatment of SLS algorithms, this book examines the general concepts and specific instances of SLS algorithms and considers their development, analysis and application.

Book Responsible Artificial Intelligence

Download or read book Responsible Artificial Intelligence written by Virginia Dignum and published by Springer Nature. This book was released on 2019-11-04 with total page 127 pages. Available in PDF, EPUB and Kindle. Book excerpt: In 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.

Book Handbook of Research on Machine Learning

Download or read book Handbook of Research on Machine Learning written by Monika Mangla and published by CRC Press. This book was released on 2022-08-04 with total page 595 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume takes the reader on a technological voyage of machine learning advancements, highlighting the systematic changes in algorithms, challenges, and constraints. The technological advancements in the ML arena have transformed and revolutionized several fields, including transportation, agriculture, finance, weather monitoring, and others. This book brings together researchers, authors, industrialists, and academicians to cover a vast selection of topics in ML, starting with the rudiments of machine learning approaches and going on to specific applications in healthcare and industrial automation. The book begins with an overview of the ethics, security and privacy issues, future directions, and challenges in machine learning as well as a systematic review of deep learning techniques and provides an understanding of building generative adversarial networks. Chapters explore predictive data analytics for health issues. The book also adds a macro dimension by highlighting the industrial applications of machine learning, such as in the steel industry, for urban information retrieval, in garbage detection, in measuring air pollution, for stock market predictions, for underwater fish detection, as a fake news predictor, and more.

Book On the path to AI

    Book Details:
  • Author : Thomas D. Grant
  • Publisher : Springer Nature
  • Release : 2020-06-02
  • ISBN : 3030435822
  • Pages : 163 pages

Download or read book On the path to AI written by Thomas D. Grant and published by Springer Nature. This book was released on 2020-06-02 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 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.

Book Fundamentals of Artificial Intelligence

Download or read book Fundamentals of Artificial Intelligence written by K.R. Chowdhary and published by Springer Nature. This book was released on 2020-04-04 with total page 730 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fundamentals 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.

Book Foundations of Machine Learning  second edition

Download or read book Foundations of Machine Learning second edition written by Mehryar Mohri and published by MIT Press. This book was released on 2018-12-25 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms. This book is a general introduction to machine learning that can serve as a textbook for graduate students and a reference for researchers. It covers fundamental modern topics in machine learning while providing the theoretical basis and conceptual tools needed for the discussion and justification of algorithms. It also describes several key aspects of the application of these algorithms. The authors aim to present novel theoretical tools and concepts while giving concise proofs even for relatively advanced topics. Foundations of Machine Learning is unique in its focus on the analysis and theory of algorithms. The first four chapters lay the theoretical foundation for what follows; subsequent chapters are mostly self-contained. Topics covered include the Probably Approximately Correct (PAC) learning framework; generalization bounds based on Rademacher complexity and VC-dimension; Support Vector Machines (SVMs); kernel methods; boosting; on-line learning; multi-class classification; ranking; regression; algorithmic stability; dimensionality reduction; learning automata and languages; and reinforcement learning. Each chapter ends with a set of exercises. Appendixes provide additional material including concise probability review. This second edition offers three new chapters, on model selection, maximum entropy models, and conditional entropy models. New material in the appendixes includes a major section on Fenchel duality, expanded coverage of concentration inequalities, and an entirely new entry on information theory. More than half of the exercises are new to this edition.

Book Learning Deep Architectures for AI

Download or read book Learning Deep Architectures for AI written by Yoshua Bengio and published by Now Publishers Inc. This book was released on 2009 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: Theoretical results suggest that in order to learn the kind of complicated functions that can represent high-level abstractions (e.g. in vision, language, and other AI-level tasks), one may need deep architectures. Deep architectures are composed of multiple levels of non-linear operations, such as in neural nets with many hidden layers or in complicated propositional formulae re-using many sub-formulae. Searching the parameter space of deep architectures is a difficult task, but learning algorithms such as those for Deep Belief Networks have recently been proposed to tackle this problem with notable success, beating the state-of-the-art in certain areas. This paper discusses the motivations and principles regarding learning algorithms for deep architectures, in particular those exploiting as building blocks unsupervised learning of single-layer models such as Restricted Boltzmann Machines, used to construct deeper models such as Deep Belief Networks.

Book Agent Technology

    Book Details:
  • Author : Nicholas R. Jennings
  • Publisher : Springer Science & Business Media
  • Release : 2012-12-06
  • ISBN : 3662036789
  • Pages : 338 pages

Download or read book Agent Technology written by Nicholas R. Jennings and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first book to provide an integrative presentation of the issues, challenges and success of designing, building and using agent applications. The chapters presented are written by internationally leading authorities in the field, with a general audience in mind. The result is a unique overview of agent technology applications, ranging from an introduction to the technical foundations to reports on dealing with specific agent systems in practice.