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Books in Computer science

The Computing collection presents a range of foundational and applied content across computer and data science, including fields such as Artificial Intelligence; Computational Modelling; Computer Networks, Computer Organization & Architecture, Computer Vision & Pattern Recognition, Data Management; Embedded Systems & Computer Engineering; HCI/User Interface Design; Information Security; Machine Learning; Network Security; Software Engineering.

  • Principles of Artificial Intelligence

    • 1st Edition
    • Nils J. Nilsson
    • English
    A classic introduction to artificial intelligence intended to bridge the gap between theory and practice, Principles of Artificial Intelligence describes fundamental AI ideas that underlie applications such as natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, and intelligent data retrieval. Rather than focusing on the subject matter of the applications, the book is organized around general computational concepts involving the kinds of data structures used, the types of operations performed on the data structures, and the properties of the control strategies used.Principles of Artificial Intelligenceevolved from the author's courses and seminars at Stanford University and University of Massachusetts, Amherst, and is suitable for text use in a senior or graduate AI course, or for individual study.

  • Readings in Artificial Intelligence and Databases

    • 1st Edition
    • John Mylopoulos + 1 more
    • English
    The interaction of database and AI technologies is crucial to such applications as data mining, active databases, and knowledge-based expert systems. This volume collects the primary readings on the interactions, actual and potential, between these two fields. The editors have chosen articles to balance significant early research and the best and most comprehensive articles from the 1980s. An in-depth introduction discusses basic research motivations, giving a survey of the history, concepts, and terminology of the interaction. Major themes, approaches and results, open issues and future directions are all discussed, including the results of a major survey conducted by the editors of current work in industry and research labs. Thirteen sections follow, each with a short introduction.Topics examined include semantic data models with emphasis on conceptual modeling techniques for databases and information systems and the integration of data model concepts in high-level data languages, definition and maintenance of integrity constraints in databases and knowledge bases, natural language front ends, object-oriented database management systems, implementation issues such as concurrency control and error recovery, and representation of time and knowledge incompleteness from the viewpoints of databases, logic programming, and AI.

  • Machine Learning Proceedings 1995

    Proceedings of the Twelfth International Conference on Machine Learning, Tahoe City, California, July 9-12 1995
    • 1st Edition
    • Armand Prieditis + 1 more
    • English
    Machine Learning: Proceedings of the Twelfth International Conference on Machine Learning covers the papers presented at the Twelfth International Conference on Machine Learning (ML95), held at the Granlibakken Resort in Tahoe City, California on July 9-12, 1995. The book focuses on the processes, methodologies, principles, and approaches involved in machine learning, including inductive logic programming algorithms, neural networks, and decision trees. The selection first offers information on the theory and applications of agnostic PAC-learning with small decision trees; reinforcement learning with function approximation; and inductive learning of reactive action models. Discussions focus on inductive logic programming algorithm, collecting instances for learning, residual gradient algorithms, direct algorithms, and learning curves for decision trees of small depth. The text then elaborates on visualizing high-dimensional structure with the incremental grid growing neural network; empirical support for winnow and weighted-majority based algorithms; and automatic selection of split criterion during tree growing based on node location. The manuscript takes a look at learning hierarchies from ambiguous natural language data, learning with rare cases and small disjuncts, learning by observation and practice, and learning collection fusion strategies for information retrieval. The selection is a valuable source of data for mathematicians and researchers interested in machine learning.

  • The Digital Guide To Software Development

    • 1st Edition
    • Christine Dickinson
    • English
    Here is the first published description of the processes and practices, tools, and methods this industry giant uses to develop its software products. This 'shirt-sleeves' guide is packed with diagrams and tables that illustrate each step in the complexsoftware development process. You'll learn all about Digital's standard 'phase review process,' the role of teams and their leaders, how CASE tools work, and how to control a project while improving productivity and product quality.

  • Machine Learning Proceedings 1992

    Proceedings of the Ninth International Workshop (ML92)
    • 1st Edition
    • Peter Edwards + 1 more
    • English
    Machine Learning: Proceedings of the Ninth International Workshop (ML92) covers the papers and posters presented at ML92, the Ninth International Machine Learning Conference, held at Aberdeen, Scotland on July 1-3, 1992. The book focuses on the advancements of practices, methodologies, approaches, and techniques in machine learning. The selection first offers information on the principal axes method for constructive induction; learning by incomplete explanations of failures in recursive domains; and eliminating redundancy in explanation-based learning. Topics include means-ends analysis search in recursive domains, description space transformation, distance metric, generating similarity matrix, and learning principal axes. The text then examines trading off consistency and efficiency in version-space induction; improving path planning with learning; finding the conservation of momentum; and learning to predict in uncertain continuous tasks. The manuscript elaborates on a teaching method for reinforcement learning, compiling prior knowledge into an explicit bias, spatial analogy and subsumption, and multistrategy learning with introspective meta-explanations. The publication also ponders on selecting typical instances in instance-based learning and temporal difference learning of backgammon strategy. The selection is a valuable source of information for researchers interested in machine learning.

  • Parallel Algorithms for Numerical Linear Algebra

    • 1st Edition
    • Volume 1
    • H. van der Vorst + 1 more
    • English
    This is the first in a new series of books presenting research results and developments concerning the theory and applications of parallel computers, including vector, pipeline, array, fifth/future generation computers, and neural computers.All aspects of high-speed computing fall within the scope of the series, e.g. algorithm design, applications, software engineering, networking, taxonomy, models and architectural trends, performance, peripheral devices.Papers in Volume One cover the main streams of parallel linear algebra: systolic array algorithms, message-passing systems, algorithms for parallel shared-memory systems, and the design of fast algorithms and implementations for vector supercomputers.

  • History of Computing in the Twentieth Century

    • 1st Edition
    • Nicholas Metropolis
    • English
    A History of Computing in the Twentieth Century focuses on the advancements in the processes, methodologies, programs, and techniques in computing. The selection first elaborates on computing developments in Cambridge, U.S.A., pioneering work on computers at Bletchley, and the COLOSSUS. Discussions focus on secrecy and priority, the first COLOSSUS, MARK II COLOSSUS, postwar developments in computing, and the HEATH ROBINSON project. The text then ponders on Turing's work at the National Physical Laboratory and the construction of Pilot ACE, DEUCE, and ACE, the Smithsonian Computer History Project, and programming in America. Topics include origins of FORTRAN, optimization techniques in FORTRAN, DEUCE computer, and the Pilot ACE. The book takes a look at the development of programming in the USSR, advancement of programming languages, and reflections on the evolution of algorithmic language. The book also examines the computer development at Manchester University, the sieve process, MANIAC project, and the ENIAC project. The selection is a valuable reference for computer science experts and researchers interested in the development of computing.

  • Information System Development Process

    Proceedings of the IFIP WG8.1 Working Conference on Information System Development Process, Como, Italy, 1-3 September, 1993
    • 1st Edition
    • Volume 30
    • N. Prakash + 2 more
    • English
    This volume aims to pave the way to a greater understanding of the information system development process. Traditionally, information systems have been perceived as a slice of real world history. This has led to a strong emphasis on the development of conceptual models, the requirements specifications of which can readily be expressed. However, the route to such an expression, or the process of development, has not received any substantial attention.It is now agreed that a study of the development process affords notable benefits. Firstly, it helps to create an understanding of what a realistic development process is and how it proceeds from an initial specification to its acceptable representation. Secondly, the nature of guidance that can be provided by the next generation of CASE tools can be substantially improved. It can be expected that these tools will cease to be mere drafting aids and consistency checking programs. Instead it is likely that they will provide a procreative environment in which the development engineer will play an important role. This tool/user symbiosis should have a beneficial impact on both the productivity of the developer and on the quality of the product.In bringing together researchers and practitioners from such diverse areas as AI, Software Engineering, Decision Support and Information Systems, it is hoped this publication will take the quest to comprehend information system development processes a significant step forwards.

  • Microprocessor Architectures

    RISC, CISC and DSP
    • 2nd Edition
    • Steve Heath
    • English
    'Why are there all these different processor architectures and what do they all mean? Which processor will I use? How should I choose it?' Given the task of selecting an architecture or design approach, both engineers and managers require a knowledge of the whole system and an explanation of the design tradeoffs and their effects. This is information that rarely appears in data sheets or user manuals. This book fills that knowledge gap.Section 1 provides a primer and history of the three basic microprocessor architectures. Section 2 describes the ways in which the architectures react with the system. Section 3 looks at some more commercial aspects such as semiconductor technology, the design cycle, and selection criteria. The appendices provide benchmarking data and binary compatibility standards. Since the first edition of this book was published, much has happened within the industry. The Power PC architecture has appeared and RISC has become a more significant challenger to CISC. The book now includes new material on Power PC, and a complete chapter devoted to understanding the RISC challenge. The examples used in the text have been based on Motorola microprocessor families, but the system considerations are also applicable to other processors. For this reason comparisons to other designs have been included, and an overview of other processors including the Intel 80x86 and Pentium, DEC Alpha, SUN Sparc, and MIPS range has been given. Steve Heath has been involved in the design and development of microprocessor based systems since 1982. These designs have included VMEbus systems, microcontrollers, IBM PCs, Apple Macintoshes, and both CISC and RISC based multiprocessor systems, while using operating systems as varied as MS-DOS, UNIX, Macintosh OS and real time kernels. An avid user of computer systems, he has written numerous articles and papers for the electronics press, as well as books from Butterworth-Heineman... including VMEbus: A Practical Companion; PowerPC: A Practical Companion; MAC User's Pocket Book; UNIX Pocket Book; Upgrading Your PC Pocket Book; Upgrading Your MAC Pocket Book; and Effective PC Networking.

  • Uncertainty in Artificial Intelligence 4

    • 1st Edition
    • Volume 9
    • T.S. Levitt + 3 more
    • English
    Clearly illustrated in this volume is the current relationship between Uncertainty and AI.It has been said that research in AI revolves around five basic questions asked relative to some particular domain: What knowledge is required? How can this knowledge be acquired? How can it be represented in a system? How should this knowledge be manipulated in order to provide intelligent behavior? How can the behavior be explained? In this volume, all of these questions are addressed. From the perspective of the relationship of uncertainty to the basic questions of AI, the book divides naturally into four sections which highlight both the strengths and weaknesses of the current state of the relationship between Uncertainty and AI.

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