Grounding Bound Founded Answer Set Programs
This work addresses efficiency challenges in BFASP solving for logic programming researchers and practitioners, representing an incremental extension of existing ASP techniques.
The paper tackles the problem of grounding Bound Founded Answer Set Programs (BFASP) by flattening complex non-ground expressions and extending bottom-up grounding and magic set transformations from ASP to BFASP, resulting in significantly reduced ground program size and improved solving efficiency.
To appear in Theory and Practice of Logic Programming (TPLP) Bound Founded Answer Set Programming (BFASP) is an extension of Answer Set Programming (ASP) that extends stable model semantics to numeric variables. While the theory of BFASP is defined on ground rules, in practice BFASP programs are written as complex non-ground expressions. Flattening of BFASP is a technique used to simplify arbitrary expressions of the language to a small and well defined set of primitive expressions. In this paper, we first show how we can flatten arbitrary BFASP rule expressions, to give equivalent BFASP programs. Next, we extend the bottom-up grounding technique and magic set transformation used by ASP to BFASP programs. Our implementation shows that for BFASP problems, these techniques can significantly reduce the ground program size, and improve subsequent solving.