Anytime Computation of Cautious Consequences in Answer Set Programming
This work addresses a bottleneck in ASP query answering for AI and logic programming researchers, offering incremental improvements to solver efficiency.
The paper tackles the problem of computing cautious consequences in Answer Set Programming (ASP), which is computationally hard and often not viable in reasonable time, by introducing anytime algorithms that produce sound answers during computation.
Query answering in Answer Set Programming (ASP) is usually solved by computing (a subset of) the cautious consequences of a logic program. This task is computationally very hard, and there are programs for which computing cautious consequences is not viable in reasonable time. However, current ASP solvers produce the (whole) set of cautious consequences only at the end of their computation. This paper reports on strategies for computing cautious consequences, also introducing anytime algorithms able to produce sound answers during the computation.