Partial Evaluation of Logic Programs in Vector Spaces
  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.
