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Morgan Kaufmann

    • Readings in Groupware and Computer-Supported Cooperative Work

      • 1st Edition
      • January 13, 1993
      • Ronald M. Baecker
      • English
      • Paperback
        9 7 8 1 5 5 8 6 0 2 4 1 0
      • eBook
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      This comprehensive introduction to the field represents the best of the published literature on groupware and computer-supported cooperative work (CSCW). The papers were chosen for their breadth of coverage of the field, their clarity of expression and presentation, their excellence in terms of technical innovation or behavioral insight, their historical significance, and their utility as sources for further reading. Taken as a whole, the papers and their introductions are a complete sourcebook to the field. This book will be useful for computer professionals involved in the development or purchase of groupware technology as well as for researchers and managers. It should also serve as a valuable text for university courses on CSCW, groupware, and human-computer interaction.

    • Physically-Based Modeling for Computer Graphics

      • 1st Edition
      • October 1, 1992
      • Ronen Barzel + 1 more
      • English
      • Hardback
        9 7 8 0 1 2 0 7 9 8 8 0 3
      • eBook
        9 7 8 0 0 8 0 9 1 6 4 4 6
      Physically-Based Modeling for Computer Graphics: A Structured Approach addresses the challenge of designing and managing the complexity of physically-based models. This book will be of interest to researchers, computer graphics practitioners, mathematicians, engineers, animators, software developers and those interested in computer implementation and simulation of mathematical models.

    • C4.5

      • 1st Edition
      • October 1, 1992
      • J. Ross Quinlan
      • English
      • Paperback
        9 7 8 1 5 5 8 6 0 2 3 8 0
      • eBook
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      Classifier systems play a major role in machine learning and knowledge-based systems, and Ross Quinlan's work on ID3 and C4.5 is widely acknowledged to have made some of the most significant contributions to their development. This book is a complete guide to the C4.5 system as implemented in C for the UNIX environment. It contains a comprehensive guide to the system's use , the source code (about 8,800 lines), and implementation notes. C4.5 starts with large sets of cases belonging to known classes. The cases, described by any mixture of nominal and numeric properties, are scrutinized for patterns that allow the classes to be reliably discriminated. These patterns are then expressed as models, in the form of decision trees or sets of if-then rules, that can be used to classify new cases, with emphasis on making the models understandable as well as accurate. The system has been applied successfully to tasks involving tens of thousands of cases described by hundreds of properties. The book starts from simple core learning methods and shows how they can be elaborated and extended to deal with typical problems such as missing data and over hitting. Advantages and disadvantages of the C4.5 approach are discussed and illustrated with several case studies. This book should be of interest to developers of classification-based intelligent systems and to students in machine learning and expert systems courses.

    • Transaction Processing

      • 1st Edition
      • September 1, 1992
      • Jim Gray + 1 more
      • English
      • Hardback
        9 7 8 1 5 5 8 6 0 1 9 0 1
      • eBook
        9 7 8 0 0 8 0 5 1 9 5 5 5
      The key to client/server computing.Transactio... processing techniques are deeply ingrained in the fields ofdatabases and operating systems and are used to monitor, control and updateinformation in modern computer systems. This book will show you how large,distributed, heterogeneous computer systems can be made to work reliably.Using transactions as a unifying conceptual framework, the authors show howto build high-performance distributed systems and high-availabilityapp... with finite budgets and risk.The authors provide detailed explanations of why various problems occur aswell as practical, usable techniques for their solution. Throughout the book,examples and techniques are drawn from the most successful commercial andresearch systems. Extensive use of compilable C code fragments demonstratesthe many transaction processing algorithms presented in the book. The bookwill be valuable to anyone interested in implementing distributed systemsor client/server architectures.

    • Pattern Recognition and Machine Learning

      • 1st Edition
      • July 14, 1992
      • Y. Anzai
      • English
      • Paperback
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      • Hardback
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      • eBook
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      This is the first text to provide a unified and self-contained introduction to visual pattern recognition and machine learning. It is useful as a general introduction to artifical intelligence and knowledge engineering, and no previous knowledge of pattern recognition or machine learning is necessary. Basic for various pattern recognition and machine learning methods. Translated from Japanese, the book also features chapter exercises, keywords, and summaries.

    • Paradigms of Artificial Intelligence Programming

      • 1st Edition
      • October 1, 1991
      • Peter Norvig
      • English
      • Paperback
        9 7 8 1 5 5 8 6 0 1 9 1 8
      • eBook
        9 7 8 0 0 8 0 5 7 1 1 5 7
      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.

    • Machine Learning

      • 1st Edition
      • July 1, 1991
      • Balas K. Natarajan
      • English
      • Paperback
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      • Hardback
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      This is the first comprehensive introduction to computational learning theory. The author's uniform presentation of fundamental results and their applications offers AI researchers a theoretical perspective on the problems they study. The book presents tools for the analysis of probabilistic models of learning, tools that crisply classify what is and is not efficiently learnable. After a general introduction to Valiant's PAC paradigm and the important notion of the Vapnik-Chervonenkis dimension, the author explores specific topics such as finite automata and neural networks. The presentation is intended for a broad audience--the author's ability to motivate and pace discussions for beginners has been praised by reviewers. Each chapter contains numerous examples and exercises, as well as a useful summary of important results. An excellent introduction to the area, suitable either for a first course, or as a component in general machine learning and advanced AI courses. Also an important reference for AI researchers.

    • The KBMT Project

      • 1st Edition
      • July 1, 1991
      • Kenneth Goodman + 1 more
      • English
      • Paperback
        9 7 8 1 5 5 8 6 0 1 2 9 1
      • eBook
        9 7 8 0 0 8 0 5 1 8 9 0 9
      Machine translation of natural languages is one of the most complex and comprehensive applications of computational linguistics and artificial intelligence. This is especially true of knowledge-based machine translation (KBMT) systems, which require many knowledge resources and processing modules to carry out the necessary levels of analysis, representation and generation of meaning and form. The number of real-world problems, tasks, and solutions involved in developing any realistic-size knowledge-based machine translation system is enormous. It is thus difficult for researchers in the field to learn what a system "really does".This book fills that need with a detailed case study of a KBMT system implemented at the Center for Machine Translation at Carnegie Mellon University. The research consists in part of the creation of a system for translation between English and Japanese. The corpora used in the project were manuals for installing and maintaining IBM personal computers (sponsorship by IBM, through its Tokyo Research Laboratory) Individual chapters describe the interlingua texts used in knowledge-based machine translation, the grammar formalism embodied in the system, the grammars and lexicons and their roles in the translation process, the process of source language analysis, an augmentation module that interactively and automatically resolves ambiguities remaining after source language analysis, and the generator, which produces target language sentences. Detailed appendices illustrate the process from analysis through generation.This book is intended for developers, researchers and advanced students in natural language processing and computational linguistics, including all those who have an interest in machine translation and machine-aided translation.

    • Foundations of Genetic Algorithms 1991 (FOGA 1)

      • 1st Edition
      • Volume 1
      • July 1, 1991
      • Gregory J.E. Rawlins
      • English
      • Hardback
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      • eBook
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      Foundations of Genetic Algorithms 1991 (FOGA 1) discusses the theoretical foundations of genetic algorithms (GA) and classifier systems. This book compiles research papers on selection and convergence, coding and representation, problem hardness, deception, classifier system design, variation and recombination, parallelization, and population divergence. Other topics include the non-uniform Walsh-schema transform; spurious correlations and premature convergence in genetic algorithms; and variable default hierarchy separation in a classifier system. The grammar-based genetic algorithm; conditions for implicit parallelism; and analysis of multi-point crossover are also elaborated. This text likewise covers the genetic algorithms for real parameter optimization and isomorphisms of genetic algorithms. This publication is a good reference for students and researchers interested in genetic algorithms.

    • Parallelism and Programming in Classifier Systems

      • 1st Edition
      • December 1, 1990
      • Stephanie Forrest
      • English
      • Paperback
        9 7 8 1 5 5 8 6 0 1 0 7 9
      • eBook
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      Parallelism and Programming in Classifier Systems deals with the computational properties of the underlying parallel machine, including computational completeness, programming and representation techniques, and efficiency of algorithms. In particular, efficient classifier system implementations of symbolic data structures and reasoning procedures are presented and analyzed in detail. The book shows how classifier systems can be used to implement a set of useful operations for the classification of knowledge in semantic networks. A subset of the KL-ONE language was chosen to demonstrate these operations. Specifically, the system performs the following tasks: (1) given the KL-ONE description of a particular semantic network, the system produces a set of production rules (classifiers) that represent the network; and (2) given the description of a new term, the system determines the proper location of the new term in the existing network. These two parts of the system are described in detail. The implementation reveals certain computational properties of classifier systems, including completeness, operations that are particularly natural and efficient, and those that are quite awkward. The book shows how high-level symbolic structures can be built up from classifier systems, and it demonstrates that the parallelism of classifier systems can be exploited to implement them efficiently. This is significant since classifier systems must construct large sophisticated models and reason about them if they are to be truly ""intelligent."" Parallel organizations are of interest to many areas of computer science, such as hardware specification, programming language design, configuration of networks of separate machines, and artificial intelligence This book concentrates on a particular type of parallel organization and a particular problem in the area of AI, but the principles that are elucidated are applicable in the wider setting of computer science.

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