Deep Q Learning
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Deep Q Learning
Deep Q-Learning (DQN) is a Reinforcement learning (RL) where agents learn to perform actions in an environment so as to maximize a reward. Q-learning was introduced by Chris Watkins in 1989, in 2014 Google DeepMind patented a DQN application that can play Atari 2600 games at like human.