ASP solvers address several reasoning tasks that go beyond the mere computation of answer sets. Among them are cautious reasoning, for modeling query entailment, and optimum answer set computation, for supporting numerical optimization. This paper reports on the recent improvements of the solver wasp, and details the algorithms and the design choices for addressing several reasoning tasks in ASP. An experimental analysis on publicly available benchmarks shows that the new version of wasp outperforms the previous one. Comparing with the state-of-the-art solver clasp, the performance of wasp is competitive in the overall for number of solved instances and average execution time
Unsatisfiable core analysis can boost the computation of optimum stable models for logic programs with weak constraints. However, current solvers employing unsatisfiable core analysis either run to completion, or provide no suboptimal stable models but the one resulting from the preliminary disjoint cores analysis. This drawback is circumvented here by introducing a progression based shrinking of the analyzed unsatisfiable cores. In fact, suboptimal stable models are possibly found while shrinking unsatisfiable cores, hence resulting into an anytime algorithm. Moreover, as confirmed empirically, unsatisfiable core analysis also benefits from the shrinking process in terms of solved instances.
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