Title
Symmetric Weighted First-Order Model Counting.
Abstract
The FO Model Counting problem (FOMC) is the following: given a sentence $\Phi$ in FO and a number $n$, compute the number of models of $\Phi$ over a domain of size $n$; 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 FO$^{3}$ formula for which FOMC is #P$_1$-complete, and the existence of a Conjunctive Query for which WFOMC is #P$_1$-complete. We also prove that all $\gamma$-acyclic queries have polynomial time data complexity. For the combined complexity, we prove that, for every fragment FO$^{k}$, $k\geq 2$, the combined complexity of FOMC (or WFOMC) is #P-complete.
Year
DOI
Venue
2014
10.1145/2745754.2745760
Proceedings of the 34th ACM Symposium on Principles of Database Systems
Field
DocType
Citations 
#SAT,Discrete mathematics,Conjunctive query,Tuple,Computer science,Inference,Markov chain,#P-complete,Database theory,Time complexity
Journal
8
PageRank 
References 
Authors
0.49
26
4
Name
Order
Citations
PageRank
Paul Beame12234176.07
Guy Van den Broeck249442.25
Eric Gribkoff3594.25
Dan Suciu496251349.54