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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.

BooksJournals

  • Distributed Artificial Intelligence

    Volume I
    • 1st Edition
    • Michael N. Huhns
    • English
    Distributed Artificial Intelligence presents a collection of papers describing the state of research in distributed artificial intelligence (DAI). DAI is concerned with the cooperative solution of problems by a decentralized group of agents. The agents may range from simple processing elements to complex entities exhibiting rational behavior. The book is organized into three parts. Part I addresses ways to develop control abstractions that efficiently guide problem-solving; communication abstractions that yield cooperation; and description abstractions that result in effective organizational structure. Part II describes architectures for developing and testing DAI systems. Part III discusses applications of DAI in manufacturing, office automation, and man-machine interactions. This book is intended for researchers, system developers, and students in artificial intelligence and related disciplines. It can also be used as a reference for students and researchers in other disciplines, such as psychology, philosophy, robotics, and distributed computing, who wish to understand the issues of DAI.

  • Radiosity and Realistic Image Synthesis

    • 1st Edition
    • Michael F. Cohen + 1 more
    • English
    The goal of image synthesis is to create, using the computer, a visual experience that is identical to what a viewer would experience when viewing a real environment. Radiosity and Realistic Image Synthesis offers the first comprehensive look at the radiosity method for image synthesis and the tools required to approach this elusive goal. Basic concepts and mathematical fundamentals underlying image synthesis and radiosity algorithms are covered thoroughly. (A basic knowledge of undergraduate calculus is assumed). The algorithms that have been developed to implement the radiosity method ranging from environment subdivision to final display are discussed. Successes and difficulties in implementing and using these algorithms are highlighted. Extensions to the basic radiosity method to include glossy surfaces, fog or smoke, and realistic light sources are also described. There are 16 pages of full colour images and over 100 illustrations to explain the development and show the results of the radiosity method. Results of applications of this new technology from a variety of fields are also included.Michael Cohen has worked in the area of realistic image synthesis since 1983 and was instrumental in the development of the radiosity method. He is currently an assistant professor of computer science at Princeton University. John Wallace is a software engineer at 3D/EYE, Inc., where he is the project leader for the development of Hewlett-Packard's ATRCore radiosity and ray tracing library. A chapter on the basic concepts of image synthesis is contributed by Patrick Hanrahan. He has worked on the topic of image synthesis at Pixar, where he was instrumental in the development of the Renderman software. He has also led research on the hierarchical methods at Princeton University, where he is an associate professor of computer science. All three authors have written numerous articles on radiosity that have appeared in the SIGGAPH proceedings and elsewhere. They have also taught the SIGGRAPH course on radiosity for 5 years.

  • Artificial Intelligence in Chemical Engineering

    • 1st Edition
    • Thomas E. Quantrille + 1 more
    • English
    Artificial intelligence (AI) is the part of computer science concerned with designing intelligent computer systems (systems that exhibit characteristics we associate with intelligence in human behavior). This book is the first published textbook of AI in chemical engineering, and provides broad and in-depth coverage of AI programming, AI principles, expert systems, and neural networks in chemical engineering. This book introduces the computational means and methodologies that are used to enable computers to perform intelligent engineering tasks. A key goal is to move beyond the principles of AI into its applications in chemical engineering. After reading this book, a chemical engineer will have a firm grounding in AI, know what chemical engineering applications of AI exist today, and understand the current challenges facing AI in engineering.

  • The System Engineers Handbook

    • 1st Edition
    • John Black
    • English
    The System Engineer's Handbook, written by the developer of the VME bus system and some of the most knowledgeable experts in the computer industry, is the most comprehensive guide available for the VME bus standard. It is the system engineer's guide to building high performance multiprocessor systems. This book contains complete copies of VME bus and VXI bus specifications and applications information, enabling a system engineer to purchase state-of-the-art board components from specialized manufacturers and assemble them into a fully-functional system.

  • Introduction to Electronic Document Management Systems

    • 1st Edition
    • Bozzano G Luisa
    • English
    Introduction to Electronic Document Management Systems provides an in-depth overview of the technology of electronic document management using modern electronic image processing. It will prove to be a key source of information for management and technical staff of organizations considering a transformation from traditional micrographics-based document storage and retrieval systems to new electronic document capture systems. It will also be useful for those organizations considering improving productivity through electronic management of large volumes of data records.

  • Case-Based Planning

    Viewing Planning as a Memory Task
    • 1st Edition
    • Kristian J. Hammond
    • English
    Perspectives in Artificial Intelligence, Volume 1: Case-Based Planning: Viewing Planning as a Memory Task focuses on the processes, methodologies, and techniques employed in viewing planning as a memory task. The publication first elaborates on planning and memory and learning from planning. Discussions focus on learning from cases, learning plans, learning to predict failures, case-based planning, structure of case-based planning, and learning from planning. The text then elaborates on planning from memory and planning Thematic Organization Packets (TOPs) and strategies, including TOPs in understanding and planning, TOPs and strategies, and function of memory. The manuscript takes a look at modifying and repairing plans, case-based planning, and planning and planners. Topics include CHEF as a program, case-based planning as planning and learning, noticing and explaining the failure, storing the plan, different situations for altering plans, and introduction of failure. The publication is a vital reference for researchers interested in viewing planning as a memory task.

  • Essentials of Artificial Intelligence

    • 1st Edition
    • Matt Ginsberg
    • English
    Since its publication, Essentials of Artificial Intelligence has beenadopted at numerous universities and colleges offering introductory AIcourses at the graduate and undergraduate levels. Based on the author'scourse at Stanford University, the book is an integrated, cohesiveintroduction to the field. The author has a fresh, entertaining writingstyle that combines clear presentations with humor and AI anecdotes. At thesame time, as an active AI researcher, he presents the materialauthoritativ... and with insight that reflects a contemporary, first handunderstanding of the field. Pedagogically designed, this book offers arange of exercises and examples.

  • Systems Engineering Using SDL-92

    • 1st Edition
    • A. Olsen
    • O. Færgemand + 3 more
    • English
    CCITT (now ITU-T) Specification and Description Language (SDL) and systems engineering (formal and informal) in SDL are considered in this publication. The latest version of the language, SDL-92 [ITU Z.100 SDL-92] is introduced. The book has been written for existing and potential users of SDL - technologists involved in the specification and engineering of systems. It offers easier learning, through examples and application, than the Z.100 Recommendation of March 1993, which gives precise technical definitions and concepts. The book has sufficient coverage of the language so that for normal use it should not be necessary to consult Z.100. For this reason, the grammars, both textual and graphical, are included, and the index makes it possible to find text on most of the language mechanisms.Chapter 1 provides an overview of specification and design of telecommunication systems. It considers the usage and scope of SDL. Chapter 2 gives an overview of the language, with an introduction of the major language elements. Chapter 3 focuses on the specification of behaviour and the information interchange between processes. Chapter 4 covers the structuring of systems in terms of instances, how these may be defined by types and how types may be organised in type/subtype hierarchies by inheritance. Parameterised types and packages of type definitions are also covered. Chapter 5 presents the part of the language that provides data types, with emphasis placed on how to use predefined data types. Chapter 6 presents the use of SDL for system engineering, with a discussion of general systems engineering principles followed by an introduction to methodologies which use SDL. The use of other languages in combination with SDL, documentation issues, naming and other lexical rules, errors and language support are considered, since they are more relevant to the use of language in engineering than when initially learning the language.

  • SDL '95 with MSC in CASE

    • 1st Edition
    • R. Braek + 1 more
    • English
    Message Sequence Charts (MSC) have had an unanticipated success, both with SDL, on its own and in conjunction with other methods and tools. Major tool vendors now offer both SDL and MSC in their tool set. This timely volume reports on the recent developments in this expanding field. Several papers deal with language issues, tools and methods for effective use of MSC. Advances in "SDL technology" are discussed, and several papers deal with the early stages of product development and how SDL may be complemented by other methods, such as OMT, to improve problem understanding and make better SDL designs. New developments in the areas of tools for verification, validation and testing are also included, together with a large number of papers on applications.

  • COLT Proceedings 1990

    • 1st Edition
    • COLT
    • English
    COLT '90 covers the proceedings of the Third Annual Workshop on Computational Learning Theory, sponsored by the ACM SIGACT/SIGART, University of Rochester, Rochester, New York on August 6-8, 1990. The book focuses on the processes, methodologies, principles, and approaches involved in computational learning theory. The selection first elaborates on inductive inference of minimal programs, learning switch configurations, computational complexity of approximating distributions by probabilistic automata, and a learning criterion for stochastic rules. The text then takes a look at inductive identification of pattern languages with restricted substitutions, learning ring-sum-expansions, sample complexity of PAC-learning using random and chosen examples, and some problems of learning with an Oracle. The book examines a mechanical method of successful scientific inquiry, boosting a weak learning algorithm by majority, and learning by distances. Discussions focus on the relation to PAC learnability, majority-vote game, boosting a weak learner by majority vote, and a paradigm of scientific inquiry. The selection is a dependable source of data for researchers interested in the computational learning theory.

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