Constraints, Lazy Constraints, or Propagators in ASP Solving: An Empirical Analysis
This work addresses a bottleneck in ASP solving for applications where grounding constraints is computationally infeasible, though it appears incremental as it compares existing strategies rather than introducing a new method.
The paper tackled the problem of expensive constraint grounding in Answer Set Programming (ASP) by systematically comparing alternative strategies to avoid instantiation, such as lazy constraints or propagators, and found strengths and weaknesses in these approaches on real and synthetic benchmarks.
Answer Set Programming (ASP) is a well-established declarative paradigm. One of the successes of ASP is the availability of efficient systems. State-of-the-art systems are based on the ground+solve approach. In some applications this approach is infeasible because the grounding of one or few constraints is expensive. In this paper, we systematically compare alternative strategies to avoid the instantiation of problematic constraints, that are based on custom extensions of the solver. Results on real and synthetic benchmarks highlight some strengths and weaknesses of the different strategies. (Under consideration for acceptance in TPLP, ICLP 2017 Special Issue.)