Attention-Based Experience Replay in Deep Q-Learning


Using neural networks as function approximators in temporal difference reinforcement problems proved to be very effective in dealing with high-dimensionality of input state space, especially in more recent developments such as Deep Q-learning. These approaches share the use of a mechanism, called experience replay, that uniformly samples the previous… (More)
DOI: 10.1145/3055635.3056621


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