Random Logic Programs: Linear Model

06/23/2014
by   Kewen Wang, et al.
0

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.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
03/08/2000

A Compiler for Ordered Logic Programs

This paper describes a system, called PLP, for compiling ordered logic p...
research
10/10/2011

Answer Sets for Logic Programs with Arbitrary Abstract Constraint Atoms

In this paper, we present two alternative approaches to defining answer ...
research
01/25/1999

Extremal problems in logic programming and stable model computation

We study the following problem: given a class of logic programs C, deter...
research
11/25/2021

Graph-based Interpretation of Normal Logic Programs

In this paper we present a dependency graph-based method for computing t...
research
04/02/2013

Disjunctive Logic Programs versus Normal Logic Programs

This paper focuses on the expressive power of disjunctive and normal log...
research
08/29/2013

Universal Approximation Using Shuffled Linear Models

This paper proposes a specific type of Local Linear Model, the Shuffled ...
research
05/09/2000

An Average Analysis of Backtracking on Random Constraint Satisfaction Problems

In this paper we propose a random CSP model, called Model GB, which is a...

Please sign up or login with your details

Forgot password? Click here to reset