Lorenzo Pantè

Open-ended Multi-agent Autocurricula via Visual Inspection of Policies with Multi-modal LLMs

Lorenzo Pantè, Andrea Fanti, Roberto Capobianco

Open-ended curricula in Reinforcement Learning (RL) aim to train generally-capable agents by identifying tasks that facilitate learning increasingly complex skills. A major challenge when designing such curricula is assessing task difficulty relative to the agent's current learni…Read more