Transferring Multi-Agent Reinforcement Learning Policies for Autonomous Driving using Sim-to-Real
Eduardo Candela,Leandro Parada,Luis Marques,Tiberiu-Andrei Georgescu,Yiannis Demiris,Panagiotis Angeloudis,Eduardo Candela,Leandro Parada,Luis Marques,Tiberiu-Andrei Georgescu,Yiannis Demiris,Panagiotis Angeloudis
Autonomous Driving requires high levels of coordination and collaboration between agents. Achieving effective coordination in multi-agent systems is a difficult task that remains largely unresolved. Multi-Agent Reinforcement Learning has arisen as a powerful method to accomplish this task because it considers the interaction between agents and also allows for decentralized training—which makes it ...
