Daniel Khapun

Unifying Unsupervised and Offline RL for Fast Adaptation Using World Models

Deep reinforcement learning has proven an effective method to solve many intricate tasks, yet it still struggles with data efficiency and generalization to novel scenarios, as required in settings such as robotics. Recent approaches to deal with this include (1) unsupervised pretraining of the agent