GitHub / junthbasnet / Playing-Pong-with-Deep-Reinforcement-Learning

🏓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.

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Topics: artificial-intelligence, credit-assignment-problem, deep-q-network, deep-reinforcement-learning, epsilon-greedy-exploration, pong-game, reinforcement-learning

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