Recently, I have completed Atari Breakout (https://arxiv.org/pdf/1312.5602.pdf) with DQN.

Similar to DQN, what are the most common deep reinforcement learning algorithms and models in 2020? It seems that DQN is outdated and policy gradients are preferred.


There are several common deep reinforcement algorithms and models apart from deep Q networks (or deep Q learning). I will list them below (along with a link to the paper that introduces them or a resource that describes them).

For an exhaustive overview of deep RL algorithms and models, you could read Deep Reinforcement Learning (2018) by Yuxi Li.

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