Communication learning is an effective way to solve complicated cooperative tasks in multi-agent reinforcement learning (MARL) domain.Graph neural network (GNN) has been widely adopt for learning the multi-agent communication and various GNN-based MARL methods have emerged.However, most of these methods are not specially designed for heterogeneous multi-agent scenarios, where agents have heterogeneous attributes or features based on different observation spaces or action sets.Without effective processing and trans…