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Random logic programs: Linear model

Published online by Cambridge University Press:  05 September 2014

KEWEN WANG ,
LIAN WEN  and
KEDIAN MU
KEWEN WANG
Affiliation:
School of Information and Communication Technology, Griffith University, Australia (e-mail: k.wang@griffith.edu.au, l.wen@griffith.edu.au)
LIAN WEN
Affiliation:
School of Information and Communication Technology, Griffith University, Australia (e-mail: k.wang@griffith.edu.au, l.wen@griffith.edu.au)
KEDIAN MU
Affiliation:
School of Mathematical Sciences, Peking University, China (e-mail: mukedian@math.pku.edu.cn)
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Abstract

This paper proposes a model, the linear model, for randomly generating logic programs with low density of rules and investigates statistical properties of such random logic programs. It is mathematically shown that the average number of answer sets for a random program converges to a constant when the number of atoms approaches infinity. Several experimental results are also reported, which justify the suitability of the linear model. It is also experimentally shown that, under this model, the size distribution of answer sets for random programs tends to a normal distribution when the number of atoms is sufficiently large.

Keywords

answer set programmingrandom logic programs
Type
Regular Papers
Information
Theory and Practice of Logic Programming , Volume 15 , Issue 6 , November 2015 , pp. 818 - 853
Copyright
Copyright © Cambridge University Press 2014 

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