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rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch

Since the advent of deep reinforcement learning for game play in 2013, and simulated robotic control shortly after, a multitude of new algorithms have flourished. Most of these are model-free algorithms which can be categorized into three families: deep Q-learning, policy gradients, and Q-value policy gradients.

View this article on https://bair.berkeley.edu/.

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