2020
Promoting Coordination through Policy Regularization in Multi-Agent Deep Reinforcement Learning
NeurIPS 2020poster
In multi-agent reinforcement learning, discovering successful collective behaviors is challenging as it requires exploring a joint action space that grows exponentially with the number of agents. While the tractability of independent agent-wise exploration is appealing, this approach fails on tasks…