Reducing Overestimation Bias in Multi-Agent Domains Using Double Centralized Critics

2 code implementations • 3 Oct 2019 • Johannes Ackermann, Volker Gabler, Takayuki Osa, Masashi Sugiyama

Finally, we investigate the application of multi-agent methods to high-dimensional robotic tasks and show that our approach can be used to learn decentralized policies in this domain.

Multi-agent Reinforcement Learning Reinforcement Learning (RL)