Journal Article10.1145/1056751.1056752
Special issue on knowledge representation
112
TL;DR: The survey hoped to elicit a clear picture of how people working in this subdiscipline understand knowledge representation research, to illuminate the issues on which current research is focused, and to catalogue what approaches and techniques are currently being developed.
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Abstract: In the fall of 1978 we decided to produce a special issue of the SIGART Newsletter devoted to a survey of current knowledge representation research. We felt that there were twe useful functions such an issue could serve. First, we hoped to elicit a clear picture of how people working in this subdiscipline understand knowledge representation research, to illuminate the issues on which current research is focused, and to catalogue what approaches and techniques are currently being developed. Second -- and this is why we envisaged the issue as a survey of many different groups and projects -- we wanted to provide a document that would enable the reader to acquire at least an approximate sense of how each of the many different research endesvours around the world fit into the field as a whole.It would of course be impossible to produce a final or definitive document accomplishing these goals: rather, we hoped that this survey could initiate a continuing dialogue on issues in representation, a project for which this newsletter seems the ideal forum. It has been many months since our original decision was made, but we are finally able to present the results of that survey. Perhaps more than anything else, it has emerged as a testament to an astounding range and variety of opinions held by many different people in many different places.The following few pages are intended as an introduction to the survey as a whole, and to this issue of the newsletter. We will briefly summarize the form that the survey took, discuss the strategies we followed in analyzing and tabulating responses, briefly review the overall sense we received from the answers that were submitted, and discuss various criticisms which were submitted along with the responses. The remainder of the volume has been designed to be roughly self-explanatory at each point, so that one may dip into it at different places at will. Certain conventions, however, particularly regarding indexing and tabulating, will also be explained in the remainder of this introduction.As editors, we are enormously grateful to the many people who devoted substantial effort to responding to our survey. It is our hope that the material presented here will be interesting and helpful to our readers, and that fruitful discussion of these and other issues will continue energetically and enthusiastically into the future.
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Citations
•Book
The knowledge level
Allen Newell
- 31 Oct 1995
TL;DR: A theory of the nature of knowledge is proposed, namely, that there is another computer system level immediately above the symbol (or program) level and knowledge itself is the processing medium at this level and the principle of rationality plays a central role.
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The knowledge level
TL;DR: In this article, a theory of the nature of knowledge and representation is proposed, namely that there is another computer system level immediately above the symbol (or program) level, and the principle of rationality plays a central role.
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The role of fuzzy logic in the management of uncertainty in expert systems
TL;DR: F fuzzy logic is suggested, which is the logic underlying approximate or, equivalently, fuzzy reasoning, which leads to various basic syllogisms which may be used as rules of combination of evidence in expert systems.
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•Book
Knowledge Representation and Reasoning
Ronald J. Brachman,Hector J. Levesque +1 more
- 01 Jan 2004
TL;DR: This landmark text takes the central concepts of knowledge representation developed over the last 50 years and illustrates them in a lucid and compelling way, and offers the first true synthesis of the field in over a decade.
Intensional Concepts in Propositional Semantic Networks
TL;DR: It is pointed out that both the networks and the psychologically based networks are prone to memory confusions about knowing unless augmented by domain-specific inference processes, or by structural information.
169
References
The concept of a linguistic variable and its application to approximate reasoning—II☆
TL;DR: Much of what constitutes the core of scientific knowledge may be regarded as a reservoir of concepts and techniques which can be drawn upon to construct mathematical models of various types of systems and thereby yield quantitative information concerning their behavior.
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Fuzzy logic and approximate reasoning
TL;DR: F fuzzy logic is used in this paper to describe an imprecise logical system, FL, in which the truth-values are fuzzy subsets of the unit interval with linguistic labels such as true, false, not true, very true, quite true, not very true and not very false, etc.
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Non-monotonic logic I
Drew McDermott,Jon Doyle +1 more
TL;DR: A model and proof theories, a proof procedure, and applications for one non-monotonic logic are developed, and it is proved the completeness of the non-Monotonic predicate calculus and the decidability of theNon- monotonic sentential calculus.
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PRUF—a meaning representation language for natural languages
TL;DR: In addition to serving as a foundation for approximate reasoning, PRUF may be employed as a language for the representation of imprecise knowledge and as a means of precisiation of fuzzy propositions expressed in a natural language.
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