exp(ASPc) : Explaining ASP Programs with Choice Atoms and Constraint Rules
This work is incremental, improving explanation capabilities for ASP programs, which could benefit users in logic programming and AI domains.
The paper tackles the problem of explaining answer set programming (ASP) programs by enhancing an existing system to support choice atoms and constraint rules, resulting in a new system called exp(ASPc) that generates explanation graphs including information about choices and constraints.
We present an enhancement of exp(ASP), a system that generates explanation graphs for a literal l - an atom a or its default negation ~a - given an answer set A of a normal logic program P, which explain why l is true (or false) given A and P. The new system, exp(ASPc), differs from exp(ASP) in that it supports choice rules and utilizes constraint rules to provide explanation graphs that include information about choices and constraints.