AINeutralarXiv – CS AI · 18h ago6/10
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Self-Paced Curriculum Reinforcement Learning for Autonomous Superbike Racing in Simulation
Researchers have developed a self-paced curriculum reinforcement learning framework for training autonomous agents to race superbikes in a physics-accurate simulator, combining Soft Actor-Critic algorithms with dynamic task progression. The approach demonstrates superior training efficiency and performance compared to traditional RL methods, establishing a new baseline for two-wheeled autonomous racing where balance and lean dynamics significantly increase complexity over four-wheeled vehicles.