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Deep Q-Networks for Intelligent Transportation Systems
The dataset is used for Deep Q-Networks (DQN) to optimize real-time traffic light control policies in emerging large-scale Intelligent Transportation Systems. -
Atari 2600 game dataset
The dataset used in the paper is the Atari 2600 game dataset, which consists of 4 consecutive 80x80 gray-scale game frames as the input to the network. -
Human-level control through deep reinforcement learning
The dataset contains data from human-level control through deep reinforcement learning.
