[1708.05866] A Brief Survey of Deep Reinforcement Learning


In this survey, the authors begin with an introduction to the general field of reinforcement learning, then progress to the main streams of value-based and policy-based methods. The survey covers central algorithms in deep reinforcement learning, including the deep Q-network, trust region policy optimisation, and asynchronous advantage actor-critic. In parallel, the authors highlight the unique advantages of deep neural networks, focusing on visual understanding via reinforcement learning.


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