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Partial Evaluation of Logic Programs in Vector Spaces

EasyChair Preprint no. 172, version 1

Versions: 12history
14 pagesPublished: May 25, 2018

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 interpretation vectors and program matrices. 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.

Keyphrases: logic program, partial evaluation, vector space

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:172,
  author = {Chiaki Sakama and Hien Nguyen and Taisuke Sato and Katsumi Inoue},
  title = {Partial Evaluation of Logic Programs in Vector Spaces},
  howpublished = {EasyChair Preprint no. 172},
  doi = {10.29007/9d61},
  year = {EasyChair, 2018}}
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