Tractable Weighted First-Order Model Counting with Bounded Treewidth Binary Evidence

Authors

  • Václav Kůla Faculty of Electrical Engineering, Czech Technical University in Prague
  • Qipeng Kuang University of Hong Kong
  • Yuyi Wang CRRC Zhuzhou Institute, China
  • Yuanhong Wang Jilin University
  • Ondřej Kuželka Faculty of Electrical Engineering, Czech Technical University in Prague

DOI:

https://doi.org/10.1609/aaai.v40i23.38994

Abstract

The Weighted First-Order Model Counting Problem (WFOMC) asks to compute the weighted sum of models of a given first-order logic sentence over a given domain. Conditioning WFOMC on evidence—fixing the truth values of a set of ground literals—has been shown impossible in time polynomial in the domain size (unless ♯P ⊆ FP) even for fragments of logic that are otherwise tractable for WFOMC without evidence. In this work, we address the barrier by restricting the binary evidence to the case where the underlying Gaifman graph has bounded treewidth. We present a polynomial-time algorithm in the domain size for computing WFOMC for the two-variable fragments ??² and ?² conditioned on such binary evidence. Furthermore, we show the applicability of our algorithm in combinatorial problems by solving the stable seating arrangement problem on bounded-treewidth graphs of bounded degree, which was an open problem. We also conducted experiments to show the scalability of our algorithm compared to the existing model counting solvers.

Published

2026-03-14

How to Cite

Kůla, V., Kuang, Q., Wang, Y., Wang, Y., & Kuželka, O. (2026). Tractable Weighted First-Order Model Counting with Bounded Treewidth Binary Evidence. Proceedings of the AAAI Conference on Artificial Intelligence, 40(23), 19198–19207. https://doi.org/10.1609/aaai.v40i23.38994

Issue

Section

AAAI Technical Track on Knowledge Representation and Reasoning