Algebraic model counting

作者：Kimmig Angelika^*; Van den Broeck Guy; De Raedt Luc

来源：Journal of Applied Logic, 2017, 22: 46-62.

DOI：10.1016/j.jal.2016.11.031

• Knowledge compilation
• Model counting
• Logic

Weighted model counting (WMC) is a well-known inference task on knowledge bases, and the basis for some of the most efficient techniques for probabilistic inference in graphical models. We introduce algebraic model counting (AMC), a generalization of WMC to a semiring structure that provides a unified view on a range of tasks and existing results. We show that AMC generalizes many well-known tasks in a variety of domains such as probabilistic inference, soft constraints and network and database analysis. Furthermore, we investigate AMC from a knowledge compilation perspective and show that all AMC tasks can be evaluated using sd-DNNF circuits, which are strictly more succinct, and thus more efficient to evaluate, than direct representations of sets of models. We identify further characteristics of AMC instances that allow for evaluation on even more succinct circuits.

• 出版日期2017-7