zbMATH — the first resource for mathematics

Foundations of a functional approach to knowledge representation. (English) Zbl 0548.68090
We present a new approach to knowledge representation where knowledge bases are characterized not in terms of the structures they use to represent knowledge, but functionally, in terms of what they can be asked or told about some domain. Starting with a representation system that can be asked questions and told facts in a full first-order logical language, we then define ask- and tell-operations over an extended language that can refer not only to the domain but to what the knowledge base knows about that domain. The major technical result is that the resulting knowledge, which now includes auto-epistemic aspects, can still be represented symbolically in first-order terms. We also consider extensions to the framework such as defaults and definitional facilities. The overall result is a formal foundation for knowledge representation which, in accordance with current principles of software design, cleanly separates functionality from implementation structure.

68T99 Artificial intelligence
68P20 Information storage and retrieval of data
68Q65 Abstract data types; algebraic specification
Full Text: DOI
[1] Newell, A., The knowledge level, AI magazine, 2, 2, 1-20, (1981)
[2] Liskov, B.; Zilles, S., Programming with abstract data types, SIGPLAN notices, 9, 4, (1974)
[3] ()
[4] Israel, D.J.; Brachman, R.J., Distinctions and confusions: A catalogue raisonne, (), 452-459
[5] Mendelson, E., ()
[6] Levesque, H.J., The interaction with incomplete knowledge bases: A formal treatment, (), 240-245
[7] Levesque, H.J., A formal treatment of incomplete knowledge bases, ()
[8] Leblanc, H., On dispensing with things and worlds, (), 241-259
[9] Levesque, H.J., A formal treatment of incomplete knowledge bases, ()
[10] Hintikka, J., ()
[11] Moore, R., Reasoning about knowledge and action, ()
[12] Israel, D.J., What’s wrong with non-monotonic logic, (), 99-101
[13] Lipski, W., On semantic issues connected with incomplete information data bases, Tods, 4, 3, (1978)
[14] McCarthy, J., Circumscription—A form of non-monotonic reasoning, Artificial intelligence, 13, 27-39, (1980) · Zbl 0435.68073
[15] Reiter, R., On closed world data bases, (), 55-76
[16] (), Special Issue on Non-Monotonic Reasoning
[17] Reiter, R., On reasoning by default, (), 210-218
[18] McDermott, D.; Doyle, J., Non-monotonic logic I, Artificial intelligence, 13, 41-72, (1980) · Zbl 0435.68074
[19] Reiter, R., A logic for default reasoning, Artificial intelligence, 13, 81-132, (1980) · Zbl 0435.68069
[20] Reiter, R.; Criscuolo, G., Some representational issues in default reasoning, () · Zbl 0523.68082
[21] Cohen, B., Understanding natural kinds, ()
[22] Brachman, R.J.; Levesque, H.J., Competence in knowledge representation, (), 189-192
[23] Israel, D.J., On interpreting network formalisms, Internat. J. comput. math., 9, 1, 1-14, (1983) · Zbl 0523.68083
[24] Stefik, M., An examination of a frame-structured representation system, (), 845-852
[25] Bobrow, D.G.; Winograd, T., An overview of \sckr1.: A knowledge representation language, Cognitive sci., 1, 1, 3-46, (1977)
[26] Rich, C., Knowledge representation languages and predicate calculus: how to have your cake and eat it too, (), 193-196
[27] Brachman, R.J.; Fikes, R.E.; Levesque, H.J., \sckrypton: A functional approach to knowledge representation, IEEE comput., 16, 10, 67-73, (1983)
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.