Fine-tuning is Not Enough: A Parallel Framework for Collaborative Imitation and Reinforcement Learning in End-to-end Autonomous Driving

1. 1Identify the limitations of imitation learning in autonomous driving
2. 2Incorporate reinforcement learning to improve performance
3. 3Implement a parallel framework for collaborative imitation and reinforcement learning
4. 4Evaluate the framework's performance and compare it to sequential fine-tuning

AI engineers and researchers working on autonomous driving systems can benefit from this framework as it improves the performance of end-to-end autonomous driving

💡 Sequential fine-tuning can introduce policy drift and lead to a performance ceiling, a parallel framework can overcome this limitation

🚗💻 Fine-tuning is not enough for autonomous driving! New parallel framework combines imitation & reinforcement learning #AI #AutonomousDriving