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# Learning Bayesian Networks with Cops and Robbers

*Proceedings of the 10th International Conference on Probabilistic Graphical Models*, PMLR 138:473-484, 2020.

#### Abstract

Constraint-based methods for learning structures of Bayesian networks are based on testing conditional independencies between variables and constructing a structure that expresses the same conditional independencies as indicated by the tests. We present a constraint-based algorithm that learns the structure of a Bayesian network by simulating a cops-and-a-robber game. The algorithm is designed for learning structures of low treewidth distributions and in such case it conducts conditional independence tests only with small conditioning sets.