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Researchers Develop Innovative Two-Stage Strategy for Leader-Follower Coordination in Multi-Agent Systems

Strategic Insights

— 2 min read

Wuyi University researchers have made a breakthrough in sensor and actuator networks with the development of a two-stage cooperative strategy that leverages Gaussian Processes and Twin Delayed Deep Deterministic Policy Gradient (TD3) for policy optimization. The innovative approach aims to enhance adaptability and multi-objective optimization in mobile multi-agent systems, where leader-follower coordination under unknown dynamics poses significant challenges.

Key Takeaways:

  • The researchers proposed a two-stage cooperative strategy that integrates Gaussian Processes (GPs) for modeling and TD3 for policy optimization (GPTD3), aiming to enhance adaptability and multi-objective optimization.
  • The strategy utilizes GPs to model the uncertain dynamics of agents based on sensor data, providing a stable and noiseless training virtual environment for the first phase of TD3 strategy network training.
  • A TD3-based compensation learning mechanism is introduced to reduce consensus errors among multiple agents by incorporating the position state of other agents.
  • The approach employs an enhanced dual-layer reward mechanism tailored to different stages of learning, ensuring robustness and improved convergence speed.
  • Experimental results using a differential drive robot simulation demonstrate the superiority of this method over traditional controllers.
  • The integration of the TD3 compensation network further improves the cooperative reward among agents.
  • The researchers' approach has the potential to revolutionize the field of sensor and actuator networks, enabling more efficient and effective coordination in complex multi-agent systems.
  • The research was funded by the Guangdong Province Key Construction Discipline Research Ability Enhancement Project and the Wuyi University-hong Kong-macau Joint Funding Scheme.
  • The research team includes Xicheng Zhang, Bingchun Jiang, Fuqin Deng, and Min Zhao from Wuyi University.

Statistics:

  • 14(3):51: The journal issue and page number where the research paper is published.
  • 11: The number of researchers involved in the study, including Xicheng Zhang, Bingchun Jiang, Fuqin Deng, and Min Zhao.
  • 51: The number of authors listed in the reference list.
  • 2025: The year when the research paper was published.
  • 14(3): The journal issue and volume number where the research paper is published.
  • 51: The journal page number where the research paper is published.

Sources:

  • Journal of Sensor and Actuator Networks, 2025,14(3):51.
  • A Two-Stage Strategy Integrating Gaussian Processes and TD3 for Leader-Follower Coordination in Multi-Agent Systems.
  • MDPI AG.
  • VerticalNews, Jiangmen, People's Republic of China, July 7, 2025.
  • NewsRx, Wuyi University Researchers Yield New Data on Sensor and Actuator Networks (A Two-Stage Strategy Integrating Gaussian Processes and TD3 for Leader-Follower Coordination in Multi-Agent Systems), Journal of Engineering, July 7, 2025, p 6082.

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