ESP: Exploiting Symmetry Prior for Multi-Agent Reinforcement Learning. (arXiv:2307.16186v2 [cs.MA] UPDATED)

Multi-agent reinforcement learning (MARL) has achieved promising results in
recent years. However, most existing reinforcement learning methods require a
large amount of data for model training. In addition, data-efficient
reinforcement learning requires the construction of strong inductive biases,
which are ignored in the current MARL approaches. Inspired by the symmetry
phenomenon in multi-agent systems, this paper proposes a framework for
exploiting prior knowledge by integrating data augmentation and a well-designed
consistency loss into the existing MARL methods. In addition, the …

arxiv biases construction current data esp inductive prior reinforcement reinforcement learning symmetry training