A Multi-Agent Control Model Based on Gene Regulatory Network

This paper tackles the challenge of collaborative control in multi-agent systems by introducing a motion control strategy based on a hierarchical gene regulatory network (GRN) model. At the GRN model’s upper layer, we define an influence area for each agent, aiding them in making autonomous decisions through the dynamics of these influence areas. The lower layer of the GRN incorporates three core behavioral principles: obstacle avoidance, aggregation, and co-directional movement, enabling self-organized, coordinated movement in multi-agent settings. The effectiveness of our approach is validated through experimental simulations in two distinct environments: a forest and a channel. The experimental results demonstrate the superiority of the proposed method in these environments.