English

Counting Markov Equivalent Directed Acyclic Graphs Consistent with Background Knowledge

Data Structures and Algorithms 2023-06-14 v2 Artificial Intelligence Computational Complexity Discrete Mathematics Machine Learning

Abstract

A polynomial-time exact algorithm for counting the number of directed acyclic graphs in a Markov equivalence class was recently given by Wien\"obst, Bannach, and Li\'skiewicz (AAAI 2021). In this paper, we consider the more general problem of counting the number of directed acyclic graphs in a Markov equivalence class when the directions of some of the edges are also fixed (this setting arises, for example, when interventional data is partially available). This problem has been shown in earlier work to be complexity-theoretically hard. In contrast, we show that the problem is nevertheless tractable in an interesting class of instances, by establishing that it is ``fixed-parameter tractable''. In particular, our counting algorithm runs in time that is bounded by a polynomial in the size of the graph, where the degree of the polynomial does \emph{not} depend upon the number of additional edges provided as input.

Keywords

Cite

@article{arxiv.2206.06744,
  title  = {Counting Markov Equivalent Directed Acyclic Graphs Consistent with Background Knowledge},
  author = {Vidya Sagar Sharma},
  journal= {arXiv preprint arXiv:2206.06744},
  year   = {2023}
}

Comments

24 pages, 1 figure, and 2 tables

R2 v1 2026-06-24T11:50:33.606Z