Colin Bellinger

Rethinking the Suitability of Reinforcement Learning Algorithms Under Practical Transfer Constraints

The wall-clock time required to train a decent policy is an important consideration for practitioners, and it is found that the sample-inefficient PPO algorithm can produce a performant policy faster than relatively more sample-efficient algorithms such as SAC and TD-MPC2, validating the common understanding of massive...