🏓Deep learning model is presented to successfully learn control policies directly from high-dimensional sensory input using reinforcement learning. The model is a convolutional neural network, trained with a variant of Q-learning, whose input is raw pixels and whose output is a value function estimating future rewards in RL Pong environment.
reinforcement-learning deep-reinforcement-learning artificial-intelligence deep-q-network pong-game epsilon-greedy-exploration credit-assignment-problem
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Updated
Mar 28, 2020 - Python