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Morgan Kaufmann

    • Machine Learning Proceedings 1992

      • 1st Edition
      • June 28, 2014
      • Peter Edwards + 1 more
      • English
      • Paperback
        9 7 8 1 5 5 8 6 0 2 4 7 2
      • eBook
        9 7 8 1 4 8 3 2 9 8 5 3 5
      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.

    • Introduction to Knowledge Systems

      • 1st Edition
      • June 28, 2014
      • Mark Stefik
      • English
      • Hardback
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      • eBook
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      Focusing on fundamental scientific and engineering issues, this book communicates the principles of building and using knowledge systems from the conceptual standpoint as well as the practical. Previous treatments of knowledge systems have focused on applications within a particular field, or on symbol-level representations, such as the use of frame and rule representations. Introduction to Knowledge Systems presents fundamentals of symbol-level representations including representations for time, space, uncertainty, and vagueness. It also compares the knowledge-level organizations for three common knowledge-intensive tasks: classification, configuration, and diagnosis. The art of building knowledge systems incorporates computer science theory, programming practice, and psychology. The scope of this book is appropriately broad, ranging from the design of hierarchical search algorithms to techniques for acquiring the task-specific knowledge needed for successful applications. Each chapter proceeds from concepts to applications, and closes with a brief tour of current research topics and open issues. Readers will come away with a solid foundation that will enable them to create real-world knowledge systems using whatever tools and programming languages are most current and appropriate.

    • Computing Perspectives

      • 1st Edition
      • June 28, 2014
      • Maurice V. Wilkes
      • English
      • Paperback
        9 7 8 1 5 5 8 6 0 3 1 7 2
      • eBook
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      In this insightful collection of essays, Maurice Wilkes shares his unique perspective on the development of computers and the current state of the art. These enlightening essays discuss the foundational ideas behind modern computing and provide a solid grounding for the appreciation of emerging computer technologies.Wilkes, one of the founders of computing, has provided enormous contributions to the development of computers, including the design and construction of the EDSAC computer and early development of programming for a stored program computer. He was responsible for the concept of microprogramming. Wilkes also wrote the first paper to appear on cache memories and was an early worker in the field of wide bandwidth local area networks. In 1992 he was awarded the prestigious Kyoto Prize for Advanced Technology.These essays will be of interest to everyone involved with computers and how they arrived at their present state. Wilkes presents his perspectives with keen historical sensibility and engineering practicality. Readers are invited to consider these observations and form their own perspectives on the present state of the computer art.

    • Readings in Computer Vision

      • 1st Edition
      • June 28, 2014
      • Martin A. Fischler + 1 more
      • English
      • Paperback
        9 7 8 0 9 3 4 6 1 3 3 3 0
      • eBook
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      The field of computer vision combines techniques from physics, mathematics, psychology, artificial intelligence, and computer science to examine how machines might construct meaningful descriptions of their surrounding environment. The editors of this volume, prominent researchers and leaders of the SRI International AI Center Perception Group, have selected sixty papers, most published since 1980, with the viewpoint that computer vision is concerned with solving seven basic problems:Reconstruct... 3D scenes from 2D imagesDecomposing images into their component partsRecognizing and assigning labels to scene objectsDeducing and describing relations among scene objectsDetermining the nature of computer architectures that can support the visual functionRepresenting abstractions in the world of computer memoryMatching stored descriptions to image representationEach chapter of this volume addresses one of these problems through an introductory discussion, which identifies major ideas and summarizes approaches, and through reprints of key research papers. Two appendices on crucial assumptions in image interpretation and on parallel architectures for vision applications, a glossary of technical terms, and a comprehensive bibliography and index complete the volume.

    • Machine Learning Proceedings 1994

      • 1st Edition
      • June 28, 2014
      • William W. Cohen
      • English
      • Paperback
        9 7 8 1 5 5 8 6 0 3 3 5 6
      • eBook
        9 7 8 1 4 8 3 2 9 8 1 8 4
      Machine Learning: Proceedings of the Eleventh International Conference covers the papers presented at the Eleventh International Conference on Machine Learning (ML94), held at New Brunswick, New Jersey on July 10-13, 1994. The book focuses on the processes, methodologies, and approaches involved in machine learning, including inductive logic programming, neural networks, and decision trees. The selection first offers information on learning recursive relations with randomly selected small training sets; improving accuracy of incorrect domain theories; and using sampling and queries to extract rules from trained neural networks. The text then takes a look at boosting and other machine learning algorithms; an incremental learning approach for completable planning; and learning disjunctive concepts by means of genetic algorithms. The publication ponders on rule induction for semantic query optimization; irrelevant features and the subset selection problem; and an efficient subsumption algorithm for inductive logic programming. The book also examines Bayesian inductive logic programming; a statistical approach to decision tree modeling; and an improved algorithm for incremental induction of decision trees. The selection is a dependable source of data for researchers interested in machine learning.

    • Introduction to Machine Learning

      • 1st Edition
      • June 28, 2014
      • Yves Kodratoff
      • English
      • Paperback
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      • eBook
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      A textbook suitable for undergraduate courses in machine learningand related topics, this book provides a broad survey of the field.Generous exercises and examples give students a firm grasp of theconcepts and techniques of this rapidly developing, challenging subject.Introduction to Machine Learning synthesizes and clarifiesthe work of leading researchers, much of which is otherwise availableonly in undigested technical reports, journals, and conference proceedings.Beginnin... with an overview suitable for undergraduate readers, Kodratoffestablishes a theoretical basis for machine learning and describesits technical concepts and major application areas. Relevant logicprogramming examples are given in Prolog.Introduction to Machine Learning is an accessible and originalintroduction to a significant research area.

    • Artificial Intelligence Planning Systems

      • 1st Edition
      • June 28, 2014
      • James Hendler
      • English
      • Paperback
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      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.

    • Machine Learning

      • 1st Edition
      • June 28, 2014
      • Yves Kodratoff + 1 more
      • English
      • Hardback
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      • Paperback
        9 7 8 1 4 9 3 3 0 6 1 0 7
      • eBook
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      Machine Learning: An Artificial Intelligence Approach, Volume III presents a sample of machine learning research representative of the period between 1986 and 1989. The book is organized into six parts. Part One introduces some general issues in the field of machine learning. Part Two presents some new developments in the area of empirical learning methods, such as flexible learning concepts, the Protos learning apprentice system, and the WITT system, which implements a form of conceptual clustering. Part Three gives an account of various analytical learning methods and how analytic learning can be applied to various specific problems. Part Four describes efforts to integrate different learning strategies. These include the UNIMEM system, which empirically discovers similarities among examples; and the DISCIPLE multistrategy system, which is capable of learning with imperfect background knowledge. Part Five provides an overview of research in the area of subsymbolic learning methods. Part Six presents two types of formal approaches to machine learning. The first is an improvement over Mitchell's version space method; the second technique deals with the learning problem faced by a robot in an unfamiliar, deterministic, finite-state environment.

    • Machine Learning Proceedings 1991

      • 1st Edition
      • June 28, 2014
      • Lawrence A. Birnbaum + 1 more
      • English
      • Paperback
        9 7 8 1 5 5 8 6 0 2 0 0 7
      • eBook
        9 7 8 1 4 8 3 2 9 8 1 7 7
      Machine Learning: Proceedings of the Eighth International Workshop (ML91) covers the papers presented at ML91, the Eighth International Workshop on Machine Learning, held at Northwestern University, Evanston, Illinois, USA, in June 1991. The book focuses on constructive induction, learning from theory and data, automated knowledge acquisition, learning in intelligent information retrieval, machine learning in engineering automation, computational models of human learning, and learning reaction strategies. The selection first offers information on design rationale capture as knowledge acquisition, a domain-independent framework for effective experimentation in planning, and knowledge refinement using a high-level, non-technical vocabulary. The text then elaborates on improving the performance of inconsistent knowledge bases via combined optimization method, flexibility of speculative refinement, and a prototype based symbolic concept learning system. Topics include using task descriptions to generate error candidates, functional descriptions of knowledge-based systems, combined optimization method, and inconsistency and related work. The book ponders on learning words from context, modeling the acquisition and improvement of motor skills, a computational model of acquisition for children's addition strategies, and computer modeling of acquisition orders in child language. The manuscript also takes a look at knowledge acquisition combining analytical and empirical techniques; designing integrated learning systems for engineering design; and machine learning for nondestructive evaluation. The selection is highly recommended for researchers interested in machine learning.

    • Readings in Human-Computer Interaction

      • 1st Edition
      • June 28, 2014
      • Ronald M. Baecker
      • English
      • Paperback
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      • eBook
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      The effectiveness of the user-computer interface has become increasingly important as computer systems have become useful tools for persons not trained in computer science. In fact, the interface is often the most important factor in the success or failure of any computer system. Dealing with the numerous subtly interrelated issues and technical, behavioral, and aesthetic considerations consumes a large and increasing share of development time and a corresponding percentage of the total code for any given application. A revision of one of the most successful books on human-computer interaction, this compilation gives students, researchers, and practitioners an overview of the significant concepts and results in the field and a comprehensive guide to the research literature. Like the first edition, this book combines reprints of key research papers and case studies with synthesizing survey material and analysis by the editors. It is significantly reorganized, updated, and enhanced; over 90% of the papers are new. An invaluable resource for systems designers, cognitive scientists, computer scientists, managers, and anyone concerned with the effectiveness of user-computer interfaces, it is also designed for use as a primary or supplementary text for graduate and advanced undergraduate courses in human-computer interaction and interface design.

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