English

Symmetric Weighted First-Order Model Counting

Databases 2015-06-02 v3 Artificial Intelligence Computational Complexity Logic in Computer Science

Abstract

The FO Model Counting problem (FOMC) is the following: given a sentence Φ\Phi in FO and a number nn, compute the number of models of Φ\Phi over a domain of size nn; the Weighted variant (WFOMC) generalizes the problem by associating a weight to each tuple and defining the weight of a model to be the product of weights of its tuples. In this paper we study the complexity of the symmetric WFOMC, where all tuples of a given relation have the same weight. Our motivation comes from an important application, inference in Knowledge Bases with soft constraints, like Markov Logic Networks, but the problem is also of independent theoretical interest. We study both the data complexity, and the combined complexity of FOMC and WFOMC. For the data complexity we prove the existence of an FO3^{3} formula for which FOMC is #P1_1-complete, and the existence of a Conjunctive Query for which WFOMC is #P1_1-complete. We also prove that all γ\gamma-acyclic queries have polynomial time data complexity. For the combined complexity, we prove that, for every fragment FOk^{k}, k2k\geq 2, the combined complexity of FOMC (or WFOMC) is #P-complete.

Keywords

Cite

@article{arxiv.1412.1505,
  title  = {Symmetric Weighted First-Order Model Counting},
  author = {Paul Beame and Guy Van den Broeck and Eric Gribkoff and Dan Suciu},
  journal= {arXiv preprint arXiv:1412.1505},
  year   = {2015}
}

Comments

To appear at PODS'15

R2 v1 2026-06-22T07:19:46.971Z