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.
Authors
- Yinya Li (ORCID: https://orcid.org/0000-0002-3535-2343)
- Guoqing Qi (ORCID: https://orcid.org/0000-0001-6785-1430)
- Andong Sheng (ORCID: https://orcid.org/0000-0001-6829-3899)
- Zhongyu Zhang (ORCID: https://orcid.org/0009-0006-1357-8268)
Institutions
- Nanjing University of Science and Technology (CN)
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