USV Path Planning Based on Adaptive Fuzzy Reward

Author:

Duan Zhenhua,Wang Guoyin,Liu Qun,Shi Yan

Publisher

Springer Nature Switzerland

Reference21 articles.

1. Ho, J., Ermon, S.: Generative adversarial imitation learning. In: Advances in Neural Information Processing Systems, vol. 29 (2016)

2. Hu, Y., Wang, W., Jia, H., Wang, Y., et al.: Learning to utilize shaping rewards: a new approach of reward shaping. Adv. Neural. Inf. Process. Syst. 33, 15931–15941 (2020)

3. Jin, C., Krishnamurthy, A., Simchowitz, M., Yu, T.: Reward-free exploration for reinforcement learning. In: International Conference on Machine Learning, pp. 4870–4879. PMLR (2020)

4. Lei, X., Zhang, Z., Dong, P.: Dynamic path planning of unknown environment based on deep reinforcement learning. J. Robot. 2018 (2018)

5. Li, L., Wu, D., Huang, Y., Yuan, Z.M.: A path planning strategy unified with a colregs collision avoidance function based on deep reinforcement learning and artificial potential field. Appl. Ocean Res. 113, 102759 (2021)

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