Description
The field of robotics has seen tremendous advances in recent years, with autonomous systemsincreasingly capable of performing complex tasks in dynamic environments. Reinforcement
learning has been a key driving force behind many of these innovations, allowing robots to
learn policies for interacting with their surroundings. Meanwhile, transformers and large
language models have revolutionized natural language processing, enabling robots to
understand and generate human-like language, making human-robot interaction more
intuitive and effective. This summer school focuses on the exciting convergence of these two
fields to enable the next generation of robots to both learn and communicate in ways that were
previously unimaginable. Participants will have the opportunity to attend lectures led by both
academic researchers and industrial experts from innovative companies working at the
forefront of robotics. The academic speakers will delve into the theoretical foundations of
reinforcement learning and language models, covering topics such as RL, policy optimization,
and the intricacies of training large-scale neural networks and LLM. The industrial speakers
will showcase practical applications and case studies, highlighting real-world use cases where
RL and LLMs are being integrated into robotic systems.
| Period | 14 Jul 2025 → 18 Jul 2025 |
|---|---|
| Event type | Course |
| Location | Padova, ItalyShow on map |
| Degree of Recognition | International |