morgan@unix.SRI.COM (Morgan Kaufmann) (10/31/90)
Morgan Kaufmann Publishers announces a new title in its Series in
Representation and Reasoning (Ronald J. Brachman, Series Editor):
REPRESENTATIONS OF COMMONSENSE KNOWLEDGE
Ernest Davis
Courant Institute for Mathematical Sciences, New York University
A central goal of artificial intelligence is to give a computer
program commonsense understanding of basic domains such as time,
space, simple laws of nature, and simple facts about human minds.
Many different systems of representation and inference have been
developed for expressing such knowledge and reasoning with it.
Representations of Commonsense Knowledge is the first thorough
study of these techniques.
The first three chapters of the book establish a general framework
in domain-independent terms, discussing methodology, deductive
logics, and theories of plausible inference. Subsequent chapters
each deal with representations and inferences in specific domains:
quantities, time, space, physics, knowledge and belief, plans and
goals, and interactions among agents. The power of these
representations in expressing world knowledge and in supporting
significant inferences is analyzed using many detailed examples.
The discussion includes both representations that have been used
in successful AI programs and those that have been developed in
purely abstract settings.
Representations of Commonsense Knowledge is an essential reference
for AI researchers and developers. It can also be used as a
textbook in advanced undergraduate or graduate courses. Each
chapter contains exercises and suggestions for further reading.
Readers who have completed it will be prepared to read original
technical papers in the area and to begin their own work in
developing useful representations for AI programs.
July, 1990
ISBN 1-55860-033-7
515 pages, hardbound
Price: $42.95 (ordering information follows table of contents)
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Table of Contents
Preface
List of Tables
List of Figures
List of Named Axioms
Chapter 1 -- Automating Commonsense
Knowledge Bases
Methodology
Implementation
The Role of Natural Language
The Role of Logic
Incomplete and Uncertain Knowledge
Vagueness
Indexical
Commonsense Reasoning in Artificial Intelligence
Philosophy
Mathematics and Commonsense Reasoning
References
Chapter 2 -- Logic
Logical Systems and Languages
Propositional Calculus
Predicate Calculus
Syntax of Predicate Calculus
Tarskian Semantics
Other Issues in First-Order Logic
Standard First-Order Notations and Theories
Operators on Sentences
Extensional Operators
Modal Logic
Possible-Worlds Semantics
Direct Use of Possible Worlds
Individuals and Modality
Syntactic Theories
Strings
Paradoxes of Self-Reference
Appendix A: Natural Deduction
References
Exercises
Chapter 3 -- Plausible Reasoning
Nonmonotonic Logic
Nonmonotonicity
Domain-Independent Rules
Circumscription
Default Theory
Preferred Models
Classical Probability Theory
Bayes's Formula
Possible-Worlds Semantics
Statistical Inference
Frequency
Independence
Independent Evidence
Maximum Entropy
Sampling
Domain-Specific Knowledge
Conclusion
References
Exercises
Chapter 4 -- Quantities and Measurements
Order
Intervals
Addition and Subtraction
Real Valued Scales
More Arithmetic
Parameters; Signs; Monotonic Relations
Derivatives
Mode Transition Networks
Qualitative Differential Equations
Orders of Magnitude
References
Exercises
Chapter 5 -- Time
Situations
Events
Temporal Reasoning: Blocks World
The Frame Problem and the Ramification Problem
The Frame Problem as a Possible Inference
Branching Time
The STRIPS Representation
Situation Calculus
Real-Valued Time
Complex States and Events
Control Structures
Modal Temporal Logic
Tracking the present Moment
References
Exercises
Chapter 6 -- Space
Spatial Inferences: Examples
Set Operations on Regions
Distance
Relative Positions
Containment and Fitting
Abutment and Overlapping
Motion
Surface Differential
Other Predicates
Knowledge Structures
Occupancy
Constructive Solid Geometry
Boundary Representation
Topological Route Maps
Configuration Spaces
The Roller Coaster
Appendix A: Coordinate Transformations
Appendix B: Going Through
References
Exercises
Chapter 7 -- Physics
The Component Model
Qualitative Process Theory
Rigid Solid Objects
Liquids
Physical Agents
References
Exercises
Chapter 8 -- Minds
Propositional Attitudes
Belief
Axioms for Belief
Possible Worlds
Syntactic Formulation
Degree of Belief
Knowledge
Knowing Whether and What
Minds and Time
Situations and Possible Worlds
Perceptions
Realistic Models of Mind
References
Exercises
Chapter 9 -- Plans and Goals
Plans as Sequences of Primitive Actions
TWEAK -- a Nonlinear Planner
Extensions
Plans and Goals as Mental States
Knowledge of Plans and Goals
Knowledge Needed for Plan Execution
Planning and Acting
Reactive Planning
Characteristic Goals
References
Exercises
Chapter 10 -- Society
Common Knowledge
Multiagent Plans
Communication
Locutionary Descriptions
Illocutionary Speech Acts
Sample Verification of a Plan of Influence
Ethics
Possession
Appendix A: Conceptual Dependency
References
Exercises
Bibliography
Glossary
Index of Names
General Index
_________________________________________________________________
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Additional titles from the Morgan Kaufmann Series in Representation
and Reasoning:
Readings in Qualitative Reasoning About Physical Systems, edited
by Daniel S. Weld (University of Washington) and Johann de Kleer
(Xerox PARC)
Probabilistic Reasoning in Intelligent Systems: Networks of
Plausible Inference, by Judea Pearl (University of California, Los
Angeles)
Readings in Uncertain Reasoning, edited by Glenn Shafer (University
of Kansas) and Judea Pearl (University of California, Los Angeles)
Readings in Planning, edited by James Allen (University of
Rochester), James Hendler (University of Maryland) and Austin Tate
(Edinburgh University)