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In this paper, we introduce methods of encoding propositional logic programsin vector spaces. Interpretations are represented by vectors and programs arerepresented by matrices. The least model of a definite program is computed bymultiplying an interpretation vector and a program matrix. To optimizecomputation in vector spaces, we provide a method of partial evaluation ofprograms using linear algebra. Partial evaluation is done by unfolding rules ina program, and it is realized in a vector space by multiplying programmatrices. We perform experiments using randomly generated programs and showthat partial evaluation has potential for realizing efficient computation inhuge scale of programs.

Partial Evaluation of Logic Programs in Vector Spaces