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Stuart Jonathan Russell, Peter Norvig
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.
Dan Jurafsky, James H. Martin
An explosion of Web-based language techniques, merging of distinct fields, availability of phone-based dialogue systems, and much more make this an exciting time in speech and language processing. The first of its kind to thoroughly cover language technology – at all levels and with all modern technologies – this book takes an empirical approach to the subject, based on applying statistical and other machine-learning algorithms to large corporations. Builds each chapter around one or more worked examples demonstrating the main idea of the chapter, usingthe examples to illustrate the relative strengths and weaknesses of various approaches. Adds coverage of statistical sequence labeling, information extraction, question answering and summarization, advanced topics in speech recognition, speech synthesis. Revises coverage of language modeling, formal grammars, statistical parsing, machine translation, and dialog processing. A useful reference for professionals in any of the areas of speech and language processing.
Christopher M. Bishop
The field of pattern recognition has undergone substantial development over the years. This book reflects these developments while providing a grounding in the basic concepts of pattern recognition and machine learning. It is aimed at advanced undergraduates or first year PhD students, as well as researchers and practitioners.
Christopher D. Manning, Hinrich Schütze
An introduction to statistical natural language processing (NLP). The text contains the theory and algorithms needed for building NLP tools. Topics covered include: mathematical and linguistic foundations; statistical methods; collocation finding; word sense disambiguation; and probalistic parsing.
Richard O. Duda, Peter E. Hart, David G. Stork
This edition has been completely revised, enlarged and formatted in two colour. It is a systematic account of the major topics in pattern recognition, based on the fundamental principles. It includes extensive examples, exercises and a solutions manual.
David Forsyth, Jean Ponce
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.
Learn how AI experts create intelligent game objects and characters with this first volume in the AI Game Programming Wisdom series. This unique collection of articles gives programmers and developers access to the insights and wisdom of over thirty AI pros. Each article delves deep into key AI game programming issues and provides insightful new ideas and techniques that can be easily integrated into your own games. Everything from general AI architectures, rule based systems, level-of-detail AI, scripting language issues, to expert systems, fuzzy logic, neural networks, and genetic algorithms are thoroughly covered. If you're a game programmer (AI/logic, front-end, user interface, tools, graphics, etc.) this comprehensive resource will help you take your skills and knowledge to the next level.
David B. Fogel
"Blondie24 tells the story of a computer that taught itself to play checkers far better than its creators ever could by emulating the principles of Darwinian evolution and discovering innovative ways to approach the game. In this year of 2001, as we remember Arthur C. Clarke's predictions, David Fogel dramatically demonstrates how evolutionary computation may enable humans to create a thinking machine far more readily than the techniques traditionally used in the study of artificial intelligence."--BOOK JACKET.
Mark A. DeLoura
For the countless tasks involved in creating a game engine there are an equal number of possible solutions. But instead of spending hours and hours trying to develop your own answers, now you can find out how the pros do it! Game Programming Gems is a hands-on, comprehensive resource packed with a variety of game programming algorithms written by experts from the game industry and edited by Mark DeLoura, former software engineering lead for Nintendo of America, Inc. and now the newly appointed editor-in-chief of Game Developer magazine. From animation and artificial intelligence to Z-buffering, lighting calculations, weather effects, curved surfaces, mutliple layer Internet gaming, to music and sound effects, all of the major techniques needed to develop a competitive game engine are covered. Game Programming Gems is written in a style accessible to individuals with a range of expertise levels. All of the source code for each algorithm is included and can be used by advanced programmers immediately. For aspiring programmers, there is a detailed tutorial to work through before attempting the code, and suggestions for possible modifications and optimizations are included as well.
Patrick Henry Winston, Berthold Horn
This third edition is a revised and expanded version of Winston and Horn's best-selling introduction to the Lisp programming language and to Lisp-based applications, many of which are possible as a result of advances in Artificial Intelligence technology. The Knowledge You Need The new edition retains the broad coverage of previous editions that has made this book popular both with beginners and with more advanced readers -- coverage ranging from the basics of the language to detailed examples showing Lisp in practice. Based on the CommonLisp standard, this book also introduces CommonLisp's object system, CLOS, and the productivity-promoting techniques enabled by object-oriented programming. Application examples drawn from expert systems, natural language interfaces, and symbolic mathematics are featured, and new applications dealing with probability bounds, project simulation, and visual object recognition are introduced. Special Features of this Edition Based on extensive teaching experience Explains key problem solving paradigms, such as search, forward chaining, and problem reduction Discusses constraint propagation, backward chaining, and key ideas in Prolog Emphasizes procedure and data abstraction, and other points of programming style and practice Covers cliches, mapping, streams, delayed evaluation, and techniques for better and faster procedure definition 0201083191B04062001
Lisp is often thought of as an academic language, but it need not be. This is the first book that introduces Lisp as a language for the real world. Practical Common Lisp presents a thorough introduction to Common Lisp, providing you with an overall understanding of the language features and how they work. Over a third of the book is devoted to practical examples, such as the core of a spam filter and a web application for browsing MP3s and streaming them via the Shoutcast protocol to any standard MP3 client software (e.g., iTunes, XMMS, or WinAmp). In other "practical" chapters, author Peter Seibel demonstrates how to build a simple but flexible in-memory database, how to parse binary files, and how to build a unit test framework in 26 lines of code.
Provides information on the core concepts of Lisp progamming, covering such topics as recursion, input/output, object-oriented programming, and macros, and offers instructions on creating complete Lisp-based games, including a text adventure, an evolution simulation, and a robot battle.
Introduction to Neural Networks in Java, Second Edition, introduces the Java programmer to the world of Neural Networks and Artificial Intelligence. Neural network architectures such as the feedforward, Hopfield, and Self Organizing Map networks are discussed. Training techniques such as Backpropagation, Genetic Algorithms and Simulated Annealing are also introduced. Practical examples are given for each neural network. Examples include the Traveling Salesman problem, handwriting recognition, financial prediction, game strategy, learning mathematical functions and special application to Internet bots. All Java source code can be downloaded online.
Robotics is becoming an increasingly popular field for hobbyists and professionals alike. The cost of the mechanics and electronics required to build a robot are low enough that almost anybody can afford it. The hardware that used to require government funding or a large university is now available to the average person. At the same time, programming is becoming a more common skill. This book combines the most sophisticated parts of robotics and programming to fill a real gap in available information. Most robotics books today use microcontrollers as the “brains” of the robots. This approach is fine for smaller, less expensive projects, but has serious limitations. When attempting to build a robot with sophisticated movements, navigation abilities, vision, and picture-capturing abilities, it is better to use a single board computer (SBC) such as Linux as the controller.
The aim of this work is to cover the basic concepts, with the key neural network models explored sufficiently deeply to allow a competent programmer to implement the networks in a language of their choice. The book is supported by a website.