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AI Research on Knowledge Representation - Dictionary of Arguments

Norvig I 437
Knowledge representation/artificial intelligence/Norvig/Russell: Complex domains such as shopping on the Internet or driving a car in traffic require (…) general and flexible representations. (…) these representations [concentrate] on general concepts - such as events, time, physical objects, and beliefs (…). (>Ontology/Artificial intelligence).
Ontology: instead of trying to represent everything, which is impossible, we will leave placeholders where new knowledge for any domain can fit in. >Beliefs/AI research, >Objects/AI research, >Events/AI research.
Norvig I 468
Early discussions of representation in AI tended to focus on “problem representation” rather than “knowledge representation.” (See, for example, Amarel’s (1968)(1) discussion of the Missionaries and Cannibals problem.) In the 1970s, AI emphasized the development of “expert systems” (also called “knowledge-based systems”) that could, if given the appropriate domain knowledge, match or exceed the performance of human experts on narrowly defined tasks. For example, the first expert system, DENDRAL (Feigenbaum et al., 1971(2); Lindsay et al., 1980(3)), interpreted the output of a mass spectrometer (a type of instrument used to analyze the structure of organic chemical compounds) as accurately as expert chemists. >Ontology/AI research, >Representation/AI research.
Norvig I 473
Minker (2001)(4) collects papers by leading researchers in knowledge representation, summarizing 40 years of work in the field. The proceedings of the international conferences on Principles of Knowledge Representation and Reasoning provide the most up-to-date sources for work in this area. Readings in Knowledge Representation (Brachman and Levesque, 1985)(5) and Formal Theories of the Commonsense World (Hobbs and Moore, 1985)(6) are excellent anthologies on knowledge representation; the former focuses more on historically important papers in representation languages and formalisms, the latter on the accumulation of the knowledge itself. Davis (1990)(7), Stefik (1995)(8), and Sowa (1999)(9) provide textbook introductions to knowledge representation, van Harmelen et al. (2007)(10) contributes a handbook, and a special issue of AI Journal covers recent progress (Davis and Morgenstern, 2004)(11). The biennial conference on Theoretical Aspects of Reasoning About Knowledge (TARK) covers applications of the theory of knowledge in AI, economics, and distributed systems.

1. Amarel, S. (1968). On representations of problems of reasoning about actions. In Michie, D.
(Ed.), Machine Intelligence 3, Vol. 3, pp. 131-171. Elsevier/North-Holland.
2. Feigenbaum, E. A., Buchanan, B. G., and Lederberg, J. (1971). On generality and problem solving:
A case study using the DENDRAL program. In Meltzer, B. and Michie, D. (Eds.), Machine Intelligence 6, pp. 165–190. Edinburgh University Press
3. Lindsay, R. K., Buchanan, B. G., Feigenbaum, E. A., and Lederberg, J. (1980). Applications of Artificial
Intelligence for Organic Chemistry: The DENDRAL Project. McGraw-Hill.
4. Minker, J. (2001). Logic-Based Artificial Intelligence. Kluwer
5. Brachman, R. J. and Levesque, H. J. (Eds.). (1985). Readings in Knowledge Representation. Morgan
6. Hobbs, J. R. and Moore, R. C. (Eds.). (1985). Formal Theories of the Commonsense World. Ablex
7. Davis, E. (1990). Representations of Commonsense Knowledge. Morgan Kaufmann
8. Stefik, M. (1995). Introduction to Knowledge Systems. Morgan Kaufmann.
9. Sowa, J. (1999). Knowledge Representation: Logical, Philosophical, and Computational Foundations.
10. van Harmelen, F., Lifschitz, V., and Porter, B. (2007). The Handbook of Knowledge Representation.
11. Davis, E. and Morgenstern, L. (2004). Introduction: Progress in formal commonsense reasoning. AIJ, 153, 1–12.

Explanation of symbols: Roman numerals indicate the source, arabic numerals indicate the page number. The corresponding books are indicated on the right hand side. ((s)…): Comment by the sender of the contribution. Translations: Dictionary of Arguments
The note [Concept/Author], [Author1]Vs[Author2] or [Author]Vs[term] resp. "problem:"/"solution:", "old:"/"new:" and "thesis:" is an addition from the Dictionary of Arguments. If a German edition is specified, the page numbers refer to this edition.
AI Research
Norvig I
Peter Norvig
Stuart J. Russell
Artificial Intelligence: A Modern Approach Upper Saddle River, NJ 2010

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Ed. Martin Schulz, access date 2022-01-28
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