On syntactically similar logic programs and sequential decompositions
This work contributes to an algebraic theory of logic programming, potentially aiding in analogical reasoning and learning, but appears incremental as it builds on prior introductions of sequential composition.
The paper tackles the problem of measuring syntactic similarity between logic programs by constructing a qualitative and algebraic notion based on sequential decompositions, and demonstrates its application in answering queries across different domains via a one-step reduction.
Rule-based reasoning is an essential part of human intelligence prominently formalized in artificial intelligence research via logic programs. Describing complex objects as the composition of elementary ones is a common strategy in computer science and science in general. The author has recently introduced the sequential composition of logic programs in the context of logic-based analogical reasoning and learning in logic programming. Motivated by these applications, in this paper we construct a qualitative and algebraic notion of syntactic logic program similarity from sequential decompositions of programs. We then show how similarity can be used to answer queries across different domains via a one-step reduction. In a broader sense, this paper is a further step towards an algebraic theory of logic programming.