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This paper describes diff-SAT, an Answer Set and SAT solver which combinesregular solving with the capability to use probabilistic clauses, facts andrules, and to sample an optimal world-view (multiset of satisfying Booleanvariable assignments or answer sets) subject to user-provided probabilisticconstraints. The sampling process minimizes a user-defined differentiableobjective function using a gradient descent based optimization method calledDifferentiable Satisfiability Solving ($\partial\mathrm{SAT}$) respectivelyDifferentiable Answer Set Programming ($\partial\mathrm{ASP}$). Use cases arei.a. probabilistic logic programming (in form of Probabilistic Answer SetProgramming), Probabilistic Boolean Satisfiability solving (PSAT), anddistribution-aware sampling of model multisets (answer sets or Booleaninterpretations).

diff-SAT -- A Software for Sampling and Probabilistic Reasoning for SAT and Answer Set Programming