CS229 Final Report Deep Q-Learning to Play Mario
نویسنده
چکیده
In this paper, I study applying applying and adjusting DeepMind’s Atari Deep Q-Learning model to train an automatic agent to play the 1985 Nintendo game Super Mario Bros. The agent learns control policies from raw pixel data using deep reinforcement learning. The model is a convolutional neural network that trained through only raw frames of the game and basic info such as score and motion.
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