Artificial Intelligence

Author: Stuart Jonathan Russell
Publisher: Prentice Hall
ISBN: 0136042597
Format: PDF
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Artificial intelligence: A Modern Approach, 3e,is ideal for one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence. It is also a valuable resource for computer professionals, linguists, and cognitive scientists interested in artificial intelligence. The revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence.

Artificial Intelligence

Author: Stuart Jonathan Russell
Publisher:
ISBN: 9780130803023
Format: PDF
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Presents a guide to artificial intelligence, covering such topics as intelligent agents, problem-solving, logical agents, planning, uncertainty, learning, and robotics.

Artificial Intelligence a Modern Approach

Author: Emilia Stones
Publisher:
ISBN: 9781635490329
Format: PDF, Mobi
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Artificial intelligence is growing field of information technology. It has transformed the world we will in. It has made the world more accessible, more social, more advanced and is developing the globe at a rapid speed. It has enabled human beings to study the minute and intricate concepts of science, has facilitated us to create better and much advanced machinery for medical and business purposes. This book contains the topics of utmost important topics with regard to artificial intelligence. It aims to provide thorough insights into this subject and give detailed information about the various uses and methods applied in this area. As this field is emerging at a rapid pace, the contents of this text will help the readers understand the modern concepts and applications of the subject.

Multiagent Systems

Author: Gerhard Weiss
Publisher: MIT Press
ISBN: 9780262731317
Format: PDF, ePub
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An introduction to multiagent systems and contemporary distributed artificial intelligence, this text provides coverage of basic topics as well as closely-related ones. It emphasizes aspects of both theory and application and includes exercises of varying degrees of difficulty.

Paradigms of Artificial Intelligence Programming

Author: Peter Norvig
Publisher: Morgan Kaufmann
ISBN: 0080571158
Format: PDF, Docs
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Paradigms of AI Programming is the first text to teach advanced Common Lisp techniques in the context of building major AI systems. By reconstructing authentic, complex AI programs using state-of-the-art Common Lisp, the book teaches students and professionals how to build and debug robust practical programs, while demonstrating superior programming style and important AI concepts. The author strongly emphasizes the practical performance issues involved in writing real working programs of significant size. Chapters on troubleshooting and efficiency are included, along with a discussion of the fundamentals of object-oriented programming and a description of the main CLOS functions. This volume is an excellent text for a course on AI programming, a useful supplement for general AI courses and an indispensable reference for the professional programmer.

Bayesian Artificial Intelligence Second Edition

Author: Kevin B. Korb
Publisher: CRC Press
ISBN: 1439815925
Format: PDF, Mobi
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Updated and expanded, Bayesian Artificial Intelligence, Second Edition provides a practical and accessible introduction to the main concepts, foundation, and applications of Bayesian networks. It focuses on both the causal discovery of networks and Bayesian inference procedures. Adopting a causal interpretation of Bayesian networks, the authors discuss the use of Bayesian networks for causal modeling. They also draw on their own applied research to illustrate various applications of the technology. New to the Second Edition New chapter on Bayesian network classifiers New section on object-oriented Bayesian networks New section that addresses foundational problems with causal discovery and Markov blanket discovery New section that covers methods of evaluating causal discovery programs Discussions of many common modeling errors New applications and case studies More coverage on the uses of causal interventions to understand and reason with causal Bayesian networks Illustrated with real case studies, the second edition of this bestseller continues to cover the groundwork of Bayesian networks. It presents the elements of Bayesian network technology, automated causal discovery, and learning probabilities from data and shows how to employ these technologies to develop probabilistic expert systems. Web Resource The book’s website at www.csse.monash.edu.au/bai/book/book.html offers a variety of supplemental materials, including example Bayesian networks and data sets. Instructors can email the authors for sample solutions to many of the problems in the text.

Artificial Intelligence for Games

Author: Ian Millington
Publisher: CRC Press
ISBN: 1498785816
Format: PDF, Docs
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Creating robust artificial intelligence is one of the greatest challenges for game developers, yet the commercial success of a game is often dependent upon the quality of the AI. In this book, Ian Millington brings extensive professional experience to the problem of improving the quality of AI in games. He describes numerous examples from real games and explores the underlying ideas through detailed case studies. He goes further to introduce many techniques little used by developers today. The book's associated web site contains a library of C++ source code and demonstration programs, and a complete commercial source code library of AI algorithms and techniques. "Artificial Intelligence for Games - 2nd edition" will be highly useful to academics teaching courses on game AI, in that it includes exercises with each chapter. It will also include new and expanded coverage of the following: AI-oriented gameplay; Behavior driven AI; Casual games (puzzle games).

Computer Vision

Author: David A. Forsyth
Publisher: Pearson Education
ISBN: 9780273764144
Format: PDF, Mobi
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Appropriate for upper-division undergraduate and graduate level courses in computer vision found in departments of computer science, computer engineering and electrical engineering, this book offers a treatment of modern computer vision methods.

Intelligent Help Systems for UNIX

Author: Stephen J. Hegner
Publisher: Springer Science & Business Media
ISBN: 9401008744
Format: PDF, Docs
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In this international collection of papers there is a wealth of knowledge on artificial intelligence (AI) and cognitive science (CS) techniques applied to the problem of providing help systems mainly for the UNIX operating system. The research described here involves the representation of technical computer concepts, but also the representation of how users conceptualise such concepts. The collection looks at computational models and systems such as UC, Yucca, and OSCON programmed in languages such as Lisp, Prolog, OPS-5, and C which have been developed to provide UNIX help. These systems range from being menu-based to ones with natural language interfaces, some providing active help, intervening when they believe the user to have misconceptions, and some based on empirical studies of what users actually do while using UNIX. Further papers investigate planning and knowledge representation where the focus is on discovering what the user wants to do, and figuring out a way to do it, as well as representing the knowledge needed to do so. There is a significant focus on natural language dialogue where consultation systems can become active, incorporating user modfelling, natural language generation and plan recognition, modelling metaphors, and users' mistaken beliefs. Much can be learned from seeing how AI and CS techniques can be investigated in depth while being applied to a real test-bed domain such as help on UNIX.