Artificial intelligence. Modern approach. Volume 2. Knowledge and reasoning in conditions of uncertainty
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In the fourth, renewed, revised and supplemented publication of this book, the field of artificial intelligence (AI) is studied and analyzed in all its vastness and depth. All modern achievements are presented here and ideas that have been formulated in studies conducted over the past fifty years, and have also been collected for two millennia in areas of knowledge that have become an incentive to the development of AI as science. Previous publications of this book became classic samples of the literature on AI and were accepted as a textbook in more than 1,400 universities of 128 countries of the world, where they were highly appreciated as a convincing result of a generalization of the results achieved in this area of science.
The book is supplemented by an extensive set of Internet resources, including exercises, software and research projects, the implementation of algorithms, as well as additional materials and links for students and teachers.
What new in the fourth edition
In the fourth edition, the reader will get acquainted with the latest technologies and concepts presented in a more unified form with a new or expanded coverage of topics as machine learning, deep training, transfer training , multi -agent systems, robotics, processing a natural language, the problem of causality, probabilistic programming, as well as confidentiality, impartiality and security of AI.
What is represented in this volume
In connection with an extremely large volume of this encyclopedic publication, its Russian -speaking version is presented in the form of a three -volume.
In this, the second volume, which has received subtitles of knowledge and reasoning in conditions of uncertainty, various aspects of the approach to the implementation of agents acting in environments close to reality are discussed: probabilistic reasoning, including time, building plans and making decisions (simple and complex), including in a multi -agent environment.
that in other volumes
In the previous volume 1, the foundations of AI theory were discussed: intellectual agents and a possible approach to solving problems: knowledge, reasoning and planning. The next volume 3 discusses the methods and possibilities of machine learning, improving the perception and implementation of autonomous devices - robots and robotic systems, including such important social aspects as justice, trust, public good and security.
About the authors
Peter Norvig, research director at Google, Inc., before - the head of its group for the development of the main algorithms of the web video. Prior to this, he led the Department of Computer Sciences in the research center of Aims, NASA, was a professor at the University of South California and a member of the Faculty of Council in Berkeley and Stanford.
The authors of this book were awarded the first award of AAAI /EAAI "Outstanding Teacher" in 2016.
In this updated and revised publication, the reader will find the most complete and relevant introduction to the theory and practice of artificial intelligence. The book sets out ideas that have been formulated in studies conducted in this area over the past fifty years, and also presented modern achievements and the latest technologies and concepts in areas such as machine learning, multi -agent systems, robotics, processing of a natural language, and probabilistic programming programming. as well as confidentiality, impartiality and security of AI. Written without excessive academicism (but quite strictly) the book will be useful to a wide circle of readers: students, graduate students and teachers of higher educational institutions, engineers, development developers, etc.
In connection with an extremely large volume of this encyclopedic publication, its Russian -speaking version is presented in the form of a three -volume. In this, the second volume, various aspects of the approach to the implementation of agents acting in environments close to reality are discussed: probabilistic reasoning, including time, building plans and making decisions (simple and complex), including in a multi -agent environment.
4th edition
The book is supplemented by an extensive set of Internet resources, including exercises, software and research projects, the implementation of algorithms, as well as additional materials and links for students and teachers.
What new in the fourth edition
In the fourth edition, the reader will get acquainted with the latest technologies and concepts presented in a more unified form with a new or expanded coverage of topics as machine learning, deep training, transfer training , multi -agent systems, robotics, processing a natural language, the problem of causality, probabilistic programming, as well as confidentiality, impartiality and security of AI.
What is represented in this volume
In connection with an extremely large volume of this encyclopedic publication, its Russian -speaking version is presented in the form of a three -volume.
In this, the second volume, which has received subtitles of knowledge and reasoning in conditions of uncertainty, various aspects of the approach to the implementation of agents acting in environments close to reality are discussed: probabilistic reasoning, including time, building plans and making decisions (simple and complex), including in a multi -agent environment.
that in other volumes
In the previous volume 1, the foundations of AI theory were discussed: intellectual agents and a possible approach to solving problems: knowledge, reasoning and planning. The next volume 3 discusses the methods and possibilities of machine learning, improving the perception and implementation of autonomous devices - robots and robotic systems, including such important social aspects as justice, trust, public good and security.
About the authors
Peter Norvig, research director at Google, Inc., before - the head of its group for the development of the main algorithms of the web video. Prior to this, he led the Department of Computer Sciences in the research center of Aims, NASA, was a professor at the University of South California and a member of the Faculty of Council in Berkeley and Stanford.
The authors of this book were awarded the first award of AAAI /EAAI "Outstanding Teacher" in 2016.
In this updated and revised publication, the reader will find the most complete and relevant introduction to the theory and practice of artificial intelligence. The book sets out ideas that have been formulated in studies conducted in this area over the past fifty years, and also presented modern achievements and the latest technologies and concepts in areas such as machine learning, multi -agent systems, robotics, processing of a natural language, and probabilistic programming programming. as well as confidentiality, impartiality and security of AI. Written without excessive academicism (but quite strictly) the book will be useful to a wide circle of readers: students, graduate students and teachers of higher educational institutions, engineers, development developers, etc.
In connection with an extremely large volume of this encyclopedic publication, its Russian -speaking version is presented in the form of a three -volume. In this, the second volume, various aspects of the approach to the implementation of agents acting in environments close to reality are discussed: probabilistic reasoning, including time, building plans and making decisions (simple and complex), including in a multi -agent environment.
4th edition
Author:
Author:Russell Stuart
Cover:
Cover:Hard
Category:
- Category:Computer & Technology
ISBN:
ISBN:978-5-907365-26-1
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