Maximum a Posteriori Policy Optimisation

ICLR 2018 Abbas AbdolmalekiJost Tobias SpringenbergYuval TassaRemi MunosNicolas HeessMartin Riedmiller

We introduce a new algorithm for reinforcement learning called Maximum aposteriori Policy Optimisation (MPO) based on coordinate ascent on a relative entropy objective. We show that several existing methods can directly be related to our derivation... (read more)

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