Commonsense knowledge representation and reasoning with fuzzy neural networks

A. Z. Kouzani; F. He; K. Sammut

doi:10.1109/ANZIIS.1996.573944

Commonsense knowledge representation and reasoning with fuzzy neural networks

A. Z. Kouzani
, F. He
, K. Sammut

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

This paper highlights the theory of commonsense knowledge in terms of representation and reasoning. A connectionist model is proposed for commonsense knowledge representation and reasoning. A generic fuzzy neuron is employed as a basic element for the connectionist model. The representation and reasoning ability of the model is described through examples.

Original language	English
Title of host publication	1996 Australian New Zealand Conference on Intelligent Information Systems. Proceedings
Subtitle of host publication	ANZIIS 96
Publisher	Institute of Electrical and Electronics Engineers
Pages	237-240
Number of pages	4
ISBN (Print)	0-7803-3667-4
DOIs	https://doi.org/10.1109/ANZIIS.1996.573944
Publication status	Published - 1996
Event	1996 Australian New Zealand Conference on Intelligent Information Systems - Adelaide, Australia Duration: 18 Nov 1996 → 20 Nov 1996

Conference

Conference	1996 Australian New Zealand Conference on Intelligent Information Systems
Abbreviated title	ANZIIS 96
Country/Territory	Australia
City	Adelaide
Period	18/11/96 → 20/11/96

Access to Document

10.1109/ANZIIS.1996.573944Licence: In Copyright

Cite this

@inproceedings{db3de6e505af4bb99c4f1a28b36cad6a,

title = "Commonsense knowledge representation and reasoning with fuzzy neural networks",

abstract = "This paper highlights the theory of commonsense knowledge in terms of representation and reasoning. A connectionist model is proposed for commonsense knowledge representation and reasoning. A generic fuzzy neuron is employed as a basic element for the connectionist model. The representation and reasoning ability of the model is described through examples.",

author = "Kouzani, \{A. Z.\} and F. He and K. Sammut",

year = "1996",

doi = "10.1109/ANZIIS.1996.573944",

language = "English",

isbn = "0-7803-3667-4",

pages = "237--240",

booktitle = "1996 Australian New Zealand Conference on Intelligent Information Systems. Proceedings",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

note = "1996 Australian New Zealand Conference on Intelligent Information Systems, ANZIIS 96 ; Conference date: 18-11-1996 Through 20-11-1996",

}

Kouzani, AZ, He, F & Sammut, K 1996, Commonsense knowledge representation and reasoning with fuzzy neural networks. in 1996 Australian New Zealand Conference on Intelligent Information Systems. Proceedings: ANZIIS 96. Institute of Electrical and Electronics Engineers, pp. 237-240, 1996 Australian New Zealand Conference on Intelligent Information Systems, Adelaide, South Australia, Australia, 18/11/96. https://doi.org/10.1109/ANZIIS.1996.573944

Commonsense knowledge representation and reasoning with fuzzy neural networks. / Kouzani, A. Z.; He, F.; Sammut, K.
1996 Australian New Zealand Conference on Intelligent Information Systems. Proceedings: ANZIIS 96. Institute of Electrical and Electronics Engineers, 1996. p. 237-240.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Commonsense knowledge representation and reasoning with fuzzy neural networks

AU - Kouzani, A. Z.

AU - He, F.

AU - Sammut, K.

PY - 1996

Y1 - 1996

N2 - This paper highlights the theory of commonsense knowledge in terms of representation and reasoning. A connectionist model is proposed for commonsense knowledge representation and reasoning. A generic fuzzy neuron is employed as a basic element for the connectionist model. The representation and reasoning ability of the model is described through examples.

AB - This paper highlights the theory of commonsense knowledge in terms of representation and reasoning. A connectionist model is proposed for commonsense knowledge representation and reasoning. A generic fuzzy neuron is employed as a basic element for the connectionist model. The representation and reasoning ability of the model is described through examples.

UR - https://www.scopus.com/pages/publications/0030393868

U2 - 10.1109/ANZIIS.1996.573944

DO - 10.1109/ANZIIS.1996.573944

M3 - Conference contribution

AN - SCOPUS:0030393868

SN - 0-7803-3667-4

SP - 237

EP - 240

BT - 1996 Australian New Zealand Conference on Intelligent Information Systems. Proceedings

PB - Institute of Electrical and Electronics Engineers

T2 - 1996 Australian New Zealand Conference on Intelligent Information Systems

Y2 - 18 November 1996 through 20 November 1996

ER -

Commonsense knowledge representation and reasoning with fuzzy neural networks

Abstract

Conference

Access to Document

Other files and links

Fingerprint

Cite this