January 2020
Intermediate to advanced
432 pages
10h 18m
English
Content preview from Hands-On Reinforcement Learning for Games
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Understanding DQN in PyTorch
Deep reinforcement learning became prominent because of the work of combining Q-learning with DL. The combination is known as deep Q-learning or DQN for Deep Q Network. This algorithm has powered some of the cutting edge examples of DRL, when Google DeepMind used it to make classic Atari games better than humans in 2012. There are many implementations of this algorithm, and Google has even patented it. The current consensus is that Google patented such a base algorithm in order to thwart patent trolls striking at little guys or developers building commercial applications with DQN. It is unlikely that Google would exercise this legally or that it would have to since this algorithm is no longer considered state ...
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