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Temporal difference learning is considered one of the most successful methods in reinforcement learning. Recent developments in deep learning have opened up a new world of opportunities. In this project, we compare classic scalar temporal difference learning with three new distributional algorithms for playing the game of 5-in-a-row using deep neural networks: distributional temporal difference le
