Cooperative Pursuit-Evasion Game for Multi-AUVs in the Ocean Current and Obstacle Environment
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-6489-5_16
Reference11 articles.
1. De Souza, C., Newbury, R., Cosgun, A., Castillo, P., Vidolov, B., Kulić, D.: Decentralized multi-agent pursuit using deep reinforcement learning. IEEE Robot. Autom. Lett. 6(3), 4552–4559 (2021)
2. Zhu, K., Zhang, T.: Deep reinforcement learning based mobile robot navigation: a review. Tsinghua Sci. Technol. 26(5), 674–691 (2021)
3. Fang, Y., Huang, Z.W., Pu, J.Y., Zhang, J.S.: AUV position tracking and trajectory control based on fast-deployed deep reinforcement learning method. Ocean Eng. 24514, 110452 (2022)
4. Xi, M., Yang, J., Wen, J., Liu, H., Li, Y., Song, H.H.: Comprehensive ocean information-enabled AUV path planning via reinforcement learning. IEEE Internet Things J. 9(18), 17440–17451 (2022)
5. Liu, L., Tian, B., Zhao, X., Zong, Q.: UAV autonomous trajectory planning in target tracking tasks via a DQN approach. In: 2019 IEEE International Conference on Real-time Computing and Robotics (RCAR), pp. 277–282 (2019)
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