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 ($\partial\mathrm{SAT}$) respectively Differentiable Answer Set Programming ($\partial\mathrm{ASP}$). 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).

中文翻译：

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diff-SAT-用于SAT和答案集编程的抽样和概率推理软件

本文介绍了diff-SAT，这是一个答案集和SAT求解器，它将常规求解与使用概率性子句，事实和规则的功能相结合，并可以根据以下条件对最优世界观（满足布尔变量分配或答案集的多个集合）进行采样：用户提供的概率约束。采样过程分别使用基于梯度下降的优化方法（分别称为“差分可满足性求解”（$ \ partial \ mathrm {SAT} $）和“差分答案集编程”（$ \ partial \ mathrm {ASP} $））来最小化用户定义的差分目标函数。用例是概率逻辑编程（以概率答案集编程的形式），概率布尔可满足性求解（PSAT）和模型多集的分布感知采样（答案集或布尔解释）。