  In this work, we propose a distributed hierarchical locomotion control
strategy for whole-body cooperation and demonstrate the potential for migration
into large numbers of agents. Our method utilizes a hierarchical structure to
break down complex tasks into smaller, manageable sub-tasks. By incorporating
spatiotemporal continuity features, we establish the sequential logic necessary
for causal inference and cooperative behaviour in sequential tasks, thereby
facilitating efficient and coordinated control strategies. Through training
within this framework, we demonstrate enhanced adaptability and cooperation,
leading to superior performance in task completion compared to the original
methods. Moreover, we construct a set of environments as the benchmark for
embodied cooperation.
