Rough sets and approximation schemes

Victor W. Marek; Miroslaw Truszczynski

doi:10.1007/978-3-540-73451-2_4

Rough sets and approximation schemes

Victor W. Marek
, Miroslaw Truszczynski

Computer Science

Producción científica: Conference contribution › revisión exhaustiva

3 Citas (Scopus)

Resumen

Approximate reasoning is used in a variety of reasoning tasks in Logic-based Artificial Intelligence. In this abstract we compare a number of such reasoning schemes and show how they relate and differ from the approach of Pawlak's Rough Sets.

Idioma original	English
Título de la publicación alojada	Rough Sets and Intelligent Systems Paradigms - International Conference, RSEISP 2007, Proceedings
Páginas	22-28
Número de páginas	7
DOI	https://doi.org/10.1007/978-3-540-73451-2_4
Estado	Published - 2007
Evento	International Conference on Rough Sets and Intelligent Systems Paradigms, RSEISP 2007 - Warsaw, Poland Duración: jun 28 2007 → jun 30 2007

Serie de la publicación

Nombre	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen	4585 LNAI
ISSN (versión impresa)	0302-9743
ISSN (versión digital)	1611-3349

Conference

Conference	International Conference on Rough Sets and Intelligent Systems Paradigms, RSEISP 2007
País/Territorio	Poland
Ciudad	Warsaw
Período	6/28/07 → 6/30/07

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

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10.1007/978-3-540-73451-2_4

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Marek, V. W., & Truszczynski, M. (2007). Rough sets and approximation schemes. En Rough Sets and Intelligent Systems Paradigms - International Conference, RSEISP 2007, Proceedings (pp. 22-28). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4585 LNAI). https://doi.org/10.1007/978-3-540-73451-2_4

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title = "Rough sets and approximation schemes",

abstract = "Approximate reasoning is used in a variety of reasoning tasks in Logic-based Artificial Intelligence. In this abstract we compare a number of such reasoning schemes and show how they relate and differ from the approach of Pawlak's Rough Sets.",

author = "Marek, \{Victor W.\} and Miroslaw Truszczynski",

note = "Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; International Conference on Rough Sets and Intelligent Systems Paradigms, RSEISP 2007 ; Conference date: 28-06-2007 Through 30-06-2007",

year = "2007",

doi = "10.1007/978-3-540-73451-2\_4",

language = "English",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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booktitle = "Rough Sets and Intelligent Systems Paradigms - International Conference, RSEISP 2007, Proceedings",

}

Marek, VW & Truszczynski, M 2007, Rough sets and approximation schemes. En Rough Sets and Intelligent Systems Paradigms - International Conference, RSEISP 2007, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4585 LNAI, pp. 22-28, International Conference on Rough Sets and Intelligent Systems Paradigms, RSEISP 2007, Warsaw, Poland, 6/28/07. https://doi.org/10.1007/978-3-540-73451-2_4

Rough sets and approximation schemes. / Marek, Victor W.; Truszczynski, Miroslaw.
Rough Sets and Intelligent Systems Paradigms - International Conference, RSEISP 2007, Proceedings. 2007. p. 22-28 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4585 LNAI).

Producción científica: Conference contribution › revisión exhaustiva

TY - GEN

T1 - Rough sets and approximation schemes

AU - Marek, Victor W.

AU - Truszczynski, Miroslaw

PY - 2007

Y1 - 2007

N2 - Approximate reasoning is used in a variety of reasoning tasks in Logic-based Artificial Intelligence. In this abstract we compare a number of such reasoning schemes and show how they relate and differ from the approach of Pawlak's Rough Sets.

AB - Approximate reasoning is used in a variety of reasoning tasks in Logic-based Artificial Intelligence. In this abstract we compare a number of such reasoning schemes and show how they relate and differ from the approach of Pawlak's Rough Sets.

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U2 - 10.1007/978-3-540-73451-2_4

DO - 10.1007/978-3-540-73451-2_4

M3 - Conference contribution

AN - SCOPUS:38048998611

SN - 9783540734505

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 22

EP - 28

BT - Rough Sets and Intelligent Systems Paradigms - International Conference, RSEISP 2007, Proceedings

T2 - International Conference on Rough Sets and Intelligent Systems Paradigms, RSEISP 2007

Y2 - 28 June 2007 through 30 June 2007

ER -

Rough sets and approximation schemes

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