Publications

Bi-level Actor-Critic for Multi-agent Coordination

Published in AAAI2020, 2020

We proposed a novel bi-level actor-critic learning method for multi-agent reinforcement learning that allows agents to have different knowledge base, while their actions still can be executed simultaneously and distributedly, and result in Stackelberg equilibrium as the solution.

Download here