Synthesising Reinforcement Learning Policies through Set-Valued Inductive Rule Learning
Youri Coppens,
Denis Steckelmacher,
Catholijn M. Jonker
et al.
Abstract:Today's advanced Reinforcement Learning algorithms produce black-box policies, that are often difficult to interpret and trust for a person. We introduce a policy distilling algorithm, building on the CN2 rule mining algorithm, that distills the policy into a rule-based decision system. At the core of our approach is the fact that an RL process does not just learn a policy, a mapping from states to actions, but also produces extra meta-information, such as action values indicating the quality of alternative ac… Show more
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