Knowledge constructions for artificial intelligence

Ahti Pietarinen

doi:10.1007/3-540-48050-1_34

Knowledge constructions for artificial intelligence

Ahti Pietarinen^*

^*Corresponding author for this work

Academy of Chinese, History, Religion and Philosophy

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

5 Citations (Scopus)

Abstract

Some new types of knowledge constructions in epistemic logic are defined, and semantics given by combining game-theoretic notions with modal models. One such notion introduced is focussed knowledge, which arises from imperfect information in quantified epistemic logics. This notion is useful in knowledge representation schemes in artificial intelligence and multi-agent systems with uncertainty. In general, in all the logics considered here, the imperfect information is seen to give rise to partiality, including partial common and partial distributed knowledge. A game-theoretic method of creating non-monotonicity will then be suggested, based on the partialised notion of 'only knowing' and inaccessible possible worlds. The overall purpose is to show the extent in which games combine with a given variety of knowledge constructions.

Original language	English
Title of host publication	Foundations of Intelligent Systems
Subtitle of host publication	13th International Symposium, ISMIS 2002, Lyon, France, June 27-29, 2002. Proceedings
Editors	Mohand-Saïd Hacid, Zbigniew W. Raś, Djamel A. Zighed, Yves Kodratoff
Publisher	Springer Berlin Heidelberg
Pages	303-311
Number of pages	9
Edition	1st
ISBN (Electronic)	9783540480501
ISBN (Print)	3540437851, 9783540437857
DOIs	https://doi.org/10.1007/3-540-48050-1_34
Publication status	Published - 12 Jun 2002
Event	13th International Symposium on Methodologies for Intelligent Systems, ISMIS 2002 - Lyon, France Duration: 27 Jun 2002 → 29 Jun 2002 https://link.springer.com/book/10.1007/3-540-48050-1

Publication series

Name	Lecture Notes in Computer Science
Volume	2366
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Name	Lecture Notes in Artificial Intelligence

Name	ISMIS: International Symposium on Methodologies for Intelligent Systems

Conference

Conference	13th International Symposium on Methodologies for Intelligent Systems, ISMIS 2002
Country/Territory	France
City	Lyon
Period	27/06/02 → 29/06/02
Internet address	https://link.springer.com/book/10.1007/3-540-48050-1

User-Defined Keywords

Knowledge Construction
Imperfect Information
World Line
Winning Strategy
Epistemic Logic

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10.1007/3-540-48050-1_34

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Pietarinen, A. (2002). Knowledge constructions for artificial intelligence. In M.-S. Hacid, Z. W. Raś, D. A. Zighed, & Y. Kodratoff (Eds.), Foundations of Intelligent Systems: 13th International Symposium, ISMIS 2002, Lyon, France, June 27-29, 2002. Proceedings (1st ed., pp. 303-311). (Lecture Notes in Computer Science; Vol. 2366), (Lecture Notes in Artificial Intelligence), (ISMIS: International Symposium on Methodologies for Intelligent Systems). Springer Berlin Heidelberg. https://doi.org/10.1007/3-540-48050-1_34

Pietarinen, Ahti. / Knowledge constructions for artificial intelligence. Foundations of Intelligent Systems: 13th International Symposium, ISMIS 2002, Lyon, France, June 27-29, 2002. Proceedings. editor / Mohand-Saïd Hacid ; Zbigniew W. Raś ; Djamel A. Zighed ; Yves Kodratoff. 1st. ed. Springer Berlin Heidelberg, 2002. pp. 303-311 (Lecture Notes in Computer Science). (Lecture Notes in Artificial Intelligence). (ISMIS: International Symposium on Methodologies for Intelligent Systems).

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Pietarinen, A 2002, Knowledge constructions for artificial intelligence. in M-S Hacid, ZW Raś, DA Zighed & Y Kodratoff (eds), Foundations of Intelligent Systems: 13th International Symposium, ISMIS 2002, Lyon, France, June 27-29, 2002. Proceedings. 1st edn, Lecture Notes in Computer Science, vol. 2366, Lecture Notes in Artificial Intelligence, ISMIS: International Symposium on Methodologies for Intelligent Systems, Springer Berlin Heidelberg, pp. 303-311, 13th International Symposium on Methodologies for Intelligent Systems, ISMIS 2002, Lyon, France, 27/06/02. https://doi.org/10.1007/3-540-48050-1_34

Knowledge constructions for artificial intelligence. / Pietarinen, Ahti.
Foundations of Intelligent Systems: 13th International Symposium, ISMIS 2002, Lyon, France, June 27-29, 2002. Proceedings. ed. / Mohand-Saïd Hacid; Zbigniew W. Raś; Djamel A. Zighed; Yves Kodratoff. 1st. ed. Springer Berlin Heidelberg, 2002. p. 303-311 (Lecture Notes in Computer Science; Vol. 2366), (Lecture Notes in Artificial Intelligence), (ISMIS: International Symposium on Methodologies for Intelligent Systems).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

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AB - Some new types of knowledge constructions in epistemic logic are defined, and semantics given by combining game-theoretic notions with modal models. One such notion introduced is focussed knowledge, which arises from imperfect information in quantified epistemic logics. This notion is useful in knowledge representation schemes in artificial intelligence and multi-agent systems with uncertainty. In general, in all the logics considered here, the imperfect information is seen to give rise to partiality, including partial common and partial distributed knowledge. A game-theoretic method of creating non-monotonicity will then be suggested, based on the partialised notion of 'only knowing' and inaccessible possible worlds. The overall purpose is to show the extent in which games combine with a given variety of knowledge constructions.

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Pietarinen A. Knowledge constructions for artificial intelligence. In Hacid MS, Raś ZW, Zighed DA, Kodratoff Y, editors, Foundations of Intelligent Systems: 13th International Symposium, ISMIS 2002, Lyon, France, June 27-29, 2002. Proceedings. 1st ed. Springer Berlin Heidelberg. 2002. p. 303-311. (Lecture Notes in Computer Science). (Lecture Notes in Artificial Intelligence). (ISMIS: International Symposium on Methodologies for Intelligent Systems). doi: 10.1007/3-540-48050-1_34

Knowledge constructions for artificial intelligence

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