Partial Evaluation of Logic Programs in Vector Spaces
Abstract
In this paper, we introduce methods of encoding propositional logic programs in vector spaces. Interpretations are represented by vectors and programs are represented by matrices. The least model of a definite program is computed by multiplying an interpretation vector and a program matrix. To optimize computation in vector spaces, we provide a method of partial evaluation of programs using linear algebra. Partial evaluation is done by unfolding rules in a program, and it is realized in a vector space by multiplying program matrices. We perform experiments using randomly generated programs and show that partial evaluation has potential for realizing efficient computation in huge scale of programs.
Cite
@article{arxiv.1811.11435,
title = {Partial Evaluation of Logic Programs in Vector Spaces},
author = {Chiaki Sakama and Hien D. Nguyen and Taisuke Sato and Katsumi Inoue},
journal= {arXiv preprint arXiv:1811.11435},
year = {2018}
}
Comments
Proceedings of the 11th Workshop on Answer Set Programming and Other Computing Paradigms 2018