Ever since researchers began noticing a slowdown in improvements to large language models using traditional training methods, ...

Multi-agent learning has made significant strides in recent years. Benefiting from deep learning, multi-agent deep reinforcement learning (MADRL) has transcended traditional limitations seen in ...

For efficient multimodal policy learning, our method includes a two-step vision-force curriculum learning (CL) scheme (Bengio et al., 2009), allowing agents to learn from a curriculum of tasks that ...

Integrating learning-based techniques, especially reinforcement learning, into robotics is promising for solving complex problems in unstructured environments. Most of the existing approaches rely on ...