Robust multi-agent team behaviors in uncertain environment via reinforcement learning - Yan, Kok Hong (Nanyang Technological University, 2022)
Many state-of-the-art cooperative multi-agent reinforcement learning (MARL) approaches, such as MADDPG, COMA, and QMIX have focused mainly on performing well in idealized scenarios. Agents face similar environmental conditions and opponents encountered during training. The resulting policies are often fragile and brittle from overfitting to the training environment. These policies cannot be easily deployed out of the laboratory.