Bozhidar Vasilev

Semi-On-Policy Training for Sample Efficient Multi-Agent Policy Gradients

2021 · arXiv (Cornell University)

Policy gradient methods are an attractive approach to multi-agent reinforcement learning problems due to their convergence properties and robustness in partially observable scenarios. However, there is a significant performance gap between state-of-the-art policy gradient and …