Deep Reinforcement Learning with Attention for Slate Markov Decision Processes with High-Dimensional States and Actions

no code implementations • 3 Dec 2015 • Peter Sunehag, Richard Evans, Gabriel Dulac-Arnold, Yori Zwols, Daniel Visentin, Ben Coppin

Further, we use deep deterministic policy gradients to learn a policy that for each position of the slate, guides attention towards the part of the action space in which the value is the highest and we only evaluate actions in this area.

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