Max Sobol Mark

Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning

2023 · arXiv (Cornell University)

A compelling use case of offline reinforcement learning (RL) is to obtain a policy initialization from existing datasets followed by fast online fine-tuning with limited interaction. However, existing offline RL methods tend to behave poorly …