Reinforcement learning has established as a powerful tool in robotics over the past few years.
This workshop will explore the latest results on using reinforcement learning for control of robots:

• Theory and methods: decentralized multi-robot control, multi-agent reinforcement learning, safe and adaptive reinforcement learning, formal guarantees of (deep) learning-based control policies;

• Applications: RL-based control of UAVs, mobile robots, autonomous cars, robotic manipulators.

The talks will present recent results in this field and highlight open challenges to be tackled by forthcoming research.