Approximate Optimal Control for Nonlinear Multi-Agent Cooperative Pursuit-Evasion Games Using Single-Network ADP

Aming to the difficulty in obtaining analytical control strategy in non-linear cooperative multi-agent pursuit escape games(MPE) using the Nash equilibrium method, an approximate optimal control strategy is proposed in this paper. Instead of the traditional actor-critic dual networks structure, each pursuer agent employs a single-critic neural network(NN) framework combined with approximate dynamic programming(ADP) to achieve near-optimal control strategy, such that the computational burden can be significantly reduced. Moreover, a new distributed operator is introduced in weight tuning law such that the control strategy doesn't need initial stability. Finally, the effectiveness of the approximate optimal control scheme is validated through a numerial simulation.

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Publication Details

Published
2025-07-04
DOI
https://doi.org/10.1109/fasta65681.2025.11139030
Primary Topic
Guidance and Control Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Approximate Optimal Control for Nonlinear Multi-Agent Cooperative Pursuit-Evasion Games Using Single-Network ADP

Yinya Li, Guoqing Qi, Andong Sheng, Zhongyu Zhang
Guidance and Control Systems
article

Approximate Optimal Control for Nonlinear Multi-Agent Cooperative Pursuit-Evasion Games Using Single-Network ADP

Yinya Li, Guoqing Qi, Andong Sheng, Zhongyu Zhang
article en

Abstract

Aming to the difficulty in obtaining analytical control strategy in non-linear cooperative multi-agent pursuit escape games(MPE) using the Nash equilibrium method, an approximate optimal control strategy is proposed in this paper. Instead of the traditional actor-critic dual networks structure, each pursuer agent employs a single-critic neural network(NN) framework combined with approximate dynamic programming(ADP) to achieve near-optimal control strategy, such that the computational burden can be significantly reduced. Moreover, a new distributed operator is introduced in weight tuning law such that the control strategy doesn't need initial stability. Finally, the effectiveness of the approximate optimal control scheme is validated through a numerial simulation.

Nanjing University of Science and Technology (CN)
Openalex Percentile: Top 67%
Guidance and Control Systems
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