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We prove that it is NP-hard to properly PAC learn decision trees with queries, resolving a longstanding open problem in learning theory (Bshouty 1993; Guijarro–Lavín–Raghavan 1999; Mehta–Raghavan 2002 ...

In this work, we propose a novel optimization approach to interpretable RL that builds decision trees. While techniques that optimize decision trees for RL do exist, they usually employ greedy ...