Counting Markov Equivalent Directed Acyclic Graphs Consistent with Background Knowledge
This provides a tractable solution for counting causal graphs with partial interventional data, which is incremental as it extends prior work on counting without fixed edges.
The paper tackles the problem of counting directed acyclic graphs in a Markov equivalence class with some edge directions fixed, which is known to be hard, and shows it is fixed-parameter tractable, with a polynomial-time algorithm where the polynomial degree does not depend on the number of fixed edges.
A polynomial-time exact algorithm for counting the number of directed acyclic graphs in a Markov equivalence class was recently given by Wienöbst, Bannach, and Liśkiewicz (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.