UC Berkeley’s FastRLAP Learns Aggressive and Effective High-Speed Driving Strategies With <20 Minutes of Real-World
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.