Diff-sat - a software for sampling and probabilistic reasoning for sat and answer set programming

作     者：Nickles, Matthias 

作者机构：School of Computer Science National University of Ireland Galway Ireland 

出 版 物：《arXiv》 (arXiv)

年 卷 期：2021年

核心收录：

主　　题：Logic programming 

摘      要：This paper describes diff-SAT, an Answer Set and SAT solver which combines regular solving with the capability to use probabilistic clauses, facts and rules, and to sample an optimal world-view (multiset of satisfying Boolean variable assignments or answer sets) subject to user-provided probabilistic constraints. The sampling process minimizes a user-defined differentiable objective function using a gradient descent based optimization method called Differentiable Satisfiability Solving (∂SAT) respectively Differentiable Answer Set Programming (∂ASP). Use cases are i.a. probabilistic logic programming (in form of Probabilistic Answer Set Programming), Probabilistic Boolean Satisfiability solving (PSAT), and distribution-aware sampling of model multisets (answer sets or Boolean interpretations). Copyright © 2021, The Authors. All rights reserved.