Partial Evaluation of Logic Programs in Vector Spaces

EasyChair Preprint 172, version 1

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

@booklet{EasyChair:172,
  author    = {Chiaki Sakama and Hien Nguyen and Taisuke Sato and Katsumi Inoue},
  title     = {Partial Evaluation of Logic Programs in Vector Spaces},
  doi       = {10.29007/9d61},
  howpublished = {EasyChair Preprint 172},
  year      = {EasyChair, 2018}}