Research Article
Rule-based Knowledge Representation Inspired from Finite Automata
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 21 - Issue 3 |
| Published: May 2011 |
| Authors: Nabil M. Hewahi |
10.5120/2493-3367
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Nabil M. Hewahi . Rule-based Knowledge Representation Inspired from Finite Automata. International Journal of Computer Applications. 21, 3 (May 2011), 14-17. DOI=10.5120/2493-3367
@article{ 10.5120/2493-3367,
author = { Nabil M. Hewahi },
title = { Rule-based Knowledge Representation Inspired from Finite Automata },
journal = { International Journal of Computer Applications },
year = { 2011 },
volume = { 21 },
number = { 3 },
pages = { 14-17 },
doi = { 10.5120/2493-3367 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2011
%A Nabil M. Hewahi
%T Rule-based Knowledge Representation Inspired from Finite Automata%T
%J International Journal of Computer Applications
%V 21
%N 3
%P 14-17
%R 10.5120/2493-3367
%I Foundation of Computer Science (FCS), NY, USA
Abstract
In this paper we present a method for rule based knowledge representation. The proposed approach is inspired from Finite Automata (FA). The inspired FA diagrams are easily used to represent rule-based system and make it more reliable structure in large complicated systems. One of the major additions that gives the proposed structure its significance is that it can represent the rules such that else case, the user text input or user menu input, and the relation and sequence of inputs are considered. The proposed diagram is called (RKRFA).
References
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- Cohen D., “Introduction to Computer Theory”, John Wiley, 1998
- Hewahi N., “ A General Rule Structure”, Information and Software Technology, 44, pp. 451-457, 2002.
- Hewahi N., “Hidden Markov Model for Censored Production Rules”,ICIT 2009, May 3-5, Amman, Jordan, 2009.
- Hewahi N., “An Intelligent Approach For Network Management Based on Hidden Markov Model”,ACIT 2010, Dec. 14-16, Libya, 2010.
- Michalski R., Winston P., “Variable Precision Logic”, Artificial Intelligence 29, pp. 121-145, 1986.
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