Exploring MBRL Lib and Reinforcement Learning Challenges

This chapter explores the MBRL Lib, a model-based reinforcement learning library created by Facebook Research, focusing on the challenges of reproducibility in RL research. It underscores the importance of a stable library for model-based RL and shares insights on engaging with historical literature to inspire modern algorithm development. Additionally, the discussion highlights advancements in compositional generalization and the role of external data sources in enhancing learning efficiency.