A Multi-Agent Motion Prediction and Tracking Method Based on Non-Cooperative Equilibrium

Yan Li, Mengyu Zhao, Huazhi Zhang, Yuanyuan Qu and Suyu Wang
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Yan Li: School of Mechanical Electronic & Information Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China
Mengyu Zhao: School of Mechanical Electronic & Information Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China
Huazhi Zhang: School of Mechanical Electronic & Information Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China
Yuanyuan Qu: School of Mechanical Electronic & Information Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China
Suyu Wang: School of Mechanical Electronic & Information Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China

Mathematics, 2022, vol. 10, issue 1, 1-17

Abstract: A Multi-Agent Motion Prediction and Tracking method based on non-cooperative equilibrium (MPT-NCE) is proposed according to the fact that some multi-agent intelligent evolution methods, like the MADDPG, lack adaptability facing unfamiliar environments, and are unable to achieve multi-agent motion prediction and tracking, although they own advantages in multi-agent intelligence. Featured by a performance discrimination module using the time difference function together with a random mutation module applying predictive learning, the MPT-NCE is capable of improving the prediction and tracking ability of the agents in the intelligent game confrontation. Two groups of multi-agent prediction and tracking experiments are conducted and the results show that compared with the MADDPG method, in the aspect of prediction ability, the MPT-NCE achieves a prediction rate at more than 90%, which is 23.52% higher and increases the whole evolution efficiency by 16.89%; in the aspect of tracking ability, the MPT-NCE promotes the convergent speed by 11.76% while facilitating the target tracking by 25.85%. The proposed MPT-NCE method shows impressive environmental adaptability and prediction and tracking ability.

Keywords: non-cooperative equilibrium; random mutation module; performance discrimination module; multi-agent prediction and tracking (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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