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Elsevier

Morgan Kaufmann

  • Design Problem Solving

    Knowledge Structures and Control Strategies
    • 1st Edition
    • David C. Brown + 1 more
    • English
    Design Problem Solving: Knowledge Structures and Control Strategies describes the application of the generic task methodology to the problem of routine design. This book discusses the generic task methodology and what constitutes the essence of the Al approach to problem solving, including the analysis of design as an information processing activity. The basic design problem solving framework, DSPL language, and AIR-CYL Air cylinder design system are also elaborated. Other topics include the high level languages based on generic tasks, structure of a Class 3 design problem solver, and failure handling in routine design. The conceptual structure for the air cylinder and improvements to DSPL system support are likewise covered in this text. This publication is beneficial to students and specialists concerned with solving design problems.

  • Principles of Semantic Networks

    Explorations in the Representation of Knowledge
    • 1st Edition
    • John F. Sowa
    • English
    Principles of Semantic Networks: Explorations in the Representation of Knowledge provides information pertinent to the theory and applications of semantic networks. This book deals with issues in knowledge representation, which discusses theoretical topics independent of particular implementations. Organized into three parts encompassing 19 chapters, this book begins with an overview of semantic network structure for representing knowledge as a pattern of interconnected nodes and arcs. This text then analyzes the concepts of subsumption and taxonomy and synthesizes a framework that integrates many previous approaches and goes beyond them to provide an account of abstract and partially defines concepts. Other chapters consider formal analyses, which treat the methods of reasoning with semantic networks and their computational complexity. This book discusses as well encoding linguistic knowledge. The final chapter deals with a formal approach to knowledge representation that builds on ideas originating outside the artificial intelligence literature in research on foundations for programming languages. This book is a valuable resource for mathematicians.

  • Interpretation of Visual Motion

    A Computational Study
    • 1st Edition
    • Muralidhara Subbarao
    • English
    Interpretation of Visual Motion: A Computational Study provides an information processing point of view to the phenomenon of visual motion. This book discusses the computational theory formulated for recovering the scene from monocular visual motion, determining the local geometry and rigid body motion of surfaces from spatio-temporal parameters of visual motion. This compilation also provides a theoretical and computational framework for future research on visual motion, both in human vision and machine vision areas. Other topics include the computation of image flow from intensity derivatives, instantaneous image flow due to rigid motion, time and space-time derivatives of image flow, and estimation of maximum absolute error. This publication is recommended for professionals and non-specialists intending to acquire knowledge of visual motion.

  • A Many-Sorted Calculus Based on Resolution and Paramodulation

    • 1st Edition
    • Christoph Walther
    • English
    A Many-Sorted Calculus Based on Resolution and Paramodulation emphasizes the utilization of advantages and concepts of many-sorted logic for resolution and paramodulation based automated theorem proving. This book considers some first-order calculus that defines how theorems from given hypotheses by pure syntactic reasoning are obtained, shifting all the semantic and implicit argumentation to the syntactic and explicit level of formal first-order reasoning. This text discusses the efficiency of many-sorted reasoning, formal preliminaries for the RP- and ?RP-calculus, and many-sorted term rewriting and unification. The completeness and soundness of the ?RP-calculus, sort theorem, and automated theorem prover for the ?RP-calculus are also elaborated. This publication is a good source for students and researchers interested in many-sorted calculus.

  • Extending Explanation-Based Learning by Generalizing the Structure of Explanations

    • 1st Edition
    • Jude W. Shavlik
    • English
    Extending Explanation-Based Learning by Generalizing the Structure of Explanations presents several fully-implemented computer systems that reflect theories of how to extend an interesting subfield of machine learning called explanation-based learning. This book discusses the need for generalizing explanation structures, relevance to research areas outside machine learning, and schema-based problem solving. The result of standard explanation-based learning, BAGGER generalization algorithm, and empirical analysis of explanation-based learning are also elaborated. This text likewise covers the effect of increased problem complexity, rule access strategies, empirical study of BAGGER2, and related work in similarity-based learning. This publication is suitable for readers interested in machine learning, especially explanation-based learning.

  • The Expected-Outcome Model of Two-Player Games

    • 1st Edition
    • Bruce Abramson
    • English
    The Expected-Outcome Model of Two-Player Games deals with the expected-outcome model of two-player games, in which the relative merit of game-tree nodes, rather than board positions, is considered. The ambiguity of static evaluation and the problems it generates in the search system are examined and the development of a domain-independent static evaluator is described. Comprised of eight chapters, this book begins with an overview of the rationale for the mathematical study of games, followed by a discussion on some previous artificial intelligence (AI) research efforts on game-trees. The next section opens with the definition of a node's expected-outcome value as the expected value of the leaves beneath it. The expected-outcome model is outlined, paying particular attention to the expected-outcome value of a game-tree node. This model was implemented on some small versions of tic-tac-toe and Othello. The book also presents results that offer strong support for both the validity of the expected-outcome model and the rationality of its underlying assumptions. This monograph is intended for specialists in AI and computer science.

  • TREAT

    A New and Efficient Match Algorithm for AI Production System
    • 1st Edition
    • Daniel P. Miranker
    • English
    TREAT: A New and Efficient Match Algorithm for AI Production Systems describes the architecture and software systems embodying the DADO machine, a parallel tree-structured computer designed to provide significant performance improvements over serial computers of comparable hardware complexity in the execution of large expert systems implemented in production system form. This book focuses on TREAT as a match algorithm for executing production systems that is presented and comparatively analyzed with the RETE match algorithm. TREAT, originally designed specifically for the DADO machine architecture, handles efficiently both temporally redundant and non-temporally redundant production system programs. This publication is suitable for developers and specialists interested in match algorithms for AI production systems.

  • Computer Organization and Design, Enhanced

    The Hardware/Software Interface
    • 5th Edition
    • David A. Patterson + 1 more
    • English
    Computer Organization and Design, Fifth Edition, moves into the post-PC era with new examples and material highlighting the emergence of mobile computing and the cloud. The book explores this generational change with updated content featuring tablet computers, cloud infrastructure, and the ARM (mobile computing devices) and x86 (cloud computing) architectures. This new edition provides in-depth coverage of parallelism with examples and content highlighting parallel hardware and software topics. It features the Intel Core i7, ARM Cortex-A8 and NVIDIA Fermi GPU as real-world examples throughout the book. It also adds a new concrete example, Going Faster, to demonstrate how understanding hardware can inspire software optimizations that improve performance by 200 times. Other topics covered include: the Eight Great Ideas of computer architecture; performance via parallelism; performance via pipelining; performance via prediction; design for Moore's Law; hierarchy of memories; abstraction to simplify design; and dependability via redundancy. The book includes a full set of updated and improved exercises as well as pop-up definitions for technical terms and concepts. Furthermore, it features interactive learning assessments that provide instant feedback in the form of true/false, multiple choice, and short essay questions. This book will appeal to professionals in computer organization and design as well as students with interest or are taking courses in this subject.

  • 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.

  • Artificial Intelligence Planning Systems

    Proceedings of the First Conference (AIPS 92)
    • 1st Edition
    • James Hendler
    • English
    Artificial Intelligence Planning Systems documents the proceedings of the First International Conference on AI Planning Systems held in College Park, Maryland on June 15-17, 1992. This book discusses the abstract probabilistic modeling of action; building symbolic primitives with continuous control routines; and systematic adaptation for case-based planning. The analysis of ABSTRIPS; conditional nonlinear planning; and building plans to monitor and exploit open-loop and closed-loop dynamics are also elaborated. This text likewise covers the modular utility representation for decision-theoretic planning; reaction and reflection in tetris; and planning in intelligent sensor fusion. Other topics include the resource-bounded adaptive agent, critical look at Knoblock's hierarchy mechanism, and traffic laws for mobile robots. This publication is beneficial to students and researchers conducting work on AI planning systems.

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