UC Berkeley’s FastRLAP Learns Aggressive and Effective High-Speed Driving Strategies With

In the new paper FastRLAP: A System for Learning High-Speed Driving via Deep RL and Autonomous Practicing, a UC Berkeley research team proposes FastRLAP (Fast Reinforcement Learning via Autonomous Practicing), a system that autonomously practices in the real world and learns aggressive maneuvers to enable effective high-speed driving.

ai artificial intelligence autonomous deep-neural-networks deep & reinforcement learning deep rl driving machine learning machine learning & data science ml paper practices reinforcement reinforcement learning research research team self-driving car speed strategies team technology uc berkeley world