Federated Transfer Reinforcement Learning for Autonomous Driving

14 Oct 2019Xinle LiangYang LiuTianjian ChenMing LiuQiang Yang

Reinforcement learning (RL) is widely used in autonomous driving tasks and training RL models typically involves in a multi-step process: pre-training RL models on simulators, uploading the pre-trained model to real-life robots, and fine-tuning the weight parameters on robot vehicles. This sequential process is extremely time-consuming and more importantly, knowledge from the fine-tuned model stays local and can not be re-used or leveraged collaboratively... (read more)

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