We present plingo, an extension of the ASP system clingo with various probabilistic reasoning modes. Plingo is centered upon LP^MLN, a probabilistic extension of ASP based on a weight scheme from Markov Logic. This choice is motivated by the fact that the core probabilistic reasoning modes can be mapped onto optimization problems and that LP^MLN may serve as a middle-ground formalism connecting to other probabilistic approaches. As a result, plingo offers three alternative frontends, for LP^MLN, P-log, and ProbLog. The corresponding input languages and reasoning modes are implemented by means of clingo's multi-shot and theory solving capabilities. The core of plingo amounts to a re-implementation of LP^MLN in terms of modern ASP technology, extended by an approximation technique based on a new method for answer set enumeration in the order of optimality. We evaluate plingo's performance empirically by comparing it to other probabilistic systems.
翻译:我们提出“方略”是ASP系统的延伸,它以各种概率推理模式为主。Plingo以LP ⁇ MLN为中心,根据Markov Logic的权重方案,ASP的概率推展。这一选择的动机是,核心概率推理模式可以被映射为优化问题,LP ⁇ MLN可以作为一种中层形式主义,与其他概率推理方法相连接。因此,Plingo为LP ⁇ MLN、P-log和ProbLog提供了三种替代的前端。相应的投入语言和推理模式是通过粘附多光子和理论解答能力实施的。“方略”的核心相当于在现代ASP技术中重新实施LP ⁇ ML,通过一种基于新回答方法的近似技术加以扩展,按照最佳程度的顺序来计算。我们通过将Plingo的绩效与其他概率系统进行比较,对它进行经验评估。