Adrià López Escoriza

Multi-Stage Manipulation with Demonstration-Augmented Reward, Policy, and World Model Learning

Long-horizon tasks in robotic manipulation present significant challenges in reinforcement learning (RL) due to the difficulty of designing dense reward functions and effectively exploring the expansive state-action space. However, despite a lack of dense rewards, these tasks often have a multi-stag…