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Logic-Based Artificial Intelligence

  • Book
  • © 2000

Overview

Editors:
  1. Jack Minker

    1. Institute for Advanced Computer Studies and Department of Computer Science, University of Maryland, USA

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Part of the book series: The Springer International Series in Engineering and Computer Science (SECS, volume 597)

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Table of contents (24 chapters)

  1. Front Matter

    Pages i-xxiii
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  2. Introduction to Logic-Based Artificial Intelligence

    1. Front Matter

      Pages 1-1
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    2. Introduction to Logic-Based Artificial Intelligence

      • Jack Minker
      Pages 3-33

  3. Commonsense Reasoning

    1. Front Matter

      Pages 35-35
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    2. Concepts of Logical AI

      • John McCarthy
      Pages 37-56

  4. Knowledge Representation

    1. Front Matter

      Pages 57-57
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    2. Two Approaches to Efficient Open-World Reasoning

      • Giuseppe De Giacomo, Hector Levesque
      Pages 59-78

    3. Declarative Problem-Solving Using the DLV System

      • Thomas Eiter, Wolfgang Faber, Nicola Leone, Gerald Pfeifer
      Pages 79-103

  5. Nonmonotonic Reasoning

    1. Front Matter

      Pages 105-105
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    2. The Role of Default Logic in Knowledge Representation

      • James P. Delgrande, Torsten Schaub
      Pages 107-126

    3. Approximations, Stable Operators, Well-Founded Fixpoints and Applications in Nonmonotonic Reasoning

      • Marc Denecker, Victor Marek, MirosÅ‚aw TruszczyÅ„ski
      Pages 127-144

  6. Logic for Causation and Actions

    1. Front Matter

      Pages 145-145
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    2. Getting to the Airport: The Oldest Planning Problem in AI

      • Vladimir Lifschitz, Norman McCain, Emilio Remolina, Armando Tacchella
      Pages 147-165

  7. Planning and Problem Solving

    1. Front Matter

      Pages 167-167
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    2. Encoding Domain and Control Knowledge for Propositional Planning

      • Henry Kautz, Bart Selman
      Pages 169-186

    3. Functional Strips: A More Flexible Language for Planning and Problem Solving

      • Héctor Geffner
      Pages 187-209

  8. Logic, Planning and High Level Robotics

    1. Front Matter

      Pages 211-211
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    2. Planning with Natural Actions in the Situation Calculus

      • Fiora Pirri, Raymond Reiter
      Pages 213-231

    3. Reinventing Shakey

      • Murray Shanahan
      Pages 233-253

  9. Logic for Agents and Actions

    1. Front Matter

      Pages 255-255
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Keywords

About this book

The use of mathematical logic as a formalism for artificial intelligence was recognized by John McCarthy in 1959 in his paper on Programs with Common Sense. In a series of papers in the 1960's he expanded upon these ideas and continues to do so to this date. It is now 41 years since the idea of using a formal mechanism for AI arose. It is therefore appropriate to consider some of the research, applications and implementations that have resulted from this idea. In early 1995 John McCarthy suggested to me that we have a workshop on Logic-Based Artificial Intelligence (LBAI). In June 1999, the Workshop on Logic-Based Artificial Intelligence was held as a consequence of McCarthy's suggestion. The workshop came about with the support of Ephraim Glinert of the National Science Foundation (IIS-9S2013S), the American Association for Artificial Intelligence who provided support for graduate students to attend, and Joseph JaJa, Director of the University of Maryland Institute for Advanced Computer Studies who provided both manpower and financial support, and the Department of Computer Science. We are grateful for their support. This book consists of refereed papers based on presentations made at the Workshop. Not all of the Workshop participants were able to contribute papers for the book. The common theme of papers at the workshop and in this book is the use of logic as a formalism to solve problems in AI.

Editors and Affiliations

  • Institute for Advanced Computer Studies and Department of Computer Science, University of Maryland, USA

    Jack Minker

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