3 accepted papers
As the deployment of autonomous agents in real-world scenarios grows, so does the interest in their application to competitive environments with other robots. Self-play in Reinforcement Learning (RL) enables agents to develop competitive strategies. However, the complexity arising from multi-agent i…
Achieving robust performance is crucial when applying deep reinforcement learning (RL) in safety critical systems. Some of the state of the art approaches try to address the problem with adversarial agents, but these agents often require expert supervision to fine tune and prevent the adversary from…
Most airdropped cargo use a combination of one or more parachutes and an impact attenuation system to land safely. The latter adds cost, weight and complexity. However, by using their legs for impact attenuation, airdropped quadruped robots may avoid the need for such a system. In this paper, variou…