Asynchronous Methods for Deep Reinforcement Learning

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For all the following models, the training complexity is proportional to O = E T Q; (1) where E is number of the training epochs, T is the number of …

@google.com arXiv:1609.03499v2 [cs.SD] 19 Sep 2016

where 1 <x t <1 and = 255. This non-linear quantization produces a significantly better reconstruction than a simple linear quantization scheme. …

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Mastering Chess and Shogi by Self-Play with a …

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Algorithms for Reinforcement Learning - Page Not Found

Figure 1: The basic reinforcement learning scenario describe the core ideas together with a large number of state of the art algorithms, followed by the discussion of their theoretical properties and …

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