Lyu, Y.; Tang, Z.; Li, Y.; Liu, B.; Deng, M.; Wu, G.
A Multi-Agent Deep Reinforcement Learning Method with Diversified Policies for Continuous Location of Express Delivery Stations Under Heterogeneous Scenarios. ISPRS Int. J. Geo-Inf. 2025, 14, 461.
https://doi.org/10.3390/ijgi14120461
AMA Style
Lyu Y, Tang Z, Li Y, Liu B, Deng M, Wu G.
A Multi-Agent Deep Reinforcement Learning Method with Diversified Policies for Continuous Location of Express Delivery Stations Under Heterogeneous Scenarios. ISPRS International Journal of Geo-Information. 2025; 14(12):461.
https://doi.org/10.3390/ijgi14120461
Chicago/Turabian Style
Lyu, Yijie, Zhongan Tang, Yalun Li, Baoju Liu, Min Deng, and Guohua Wu.
2025. "A Multi-Agent Deep Reinforcement Learning Method with Diversified Policies for Continuous Location of Express Delivery Stations Under Heterogeneous Scenarios" ISPRS International Journal of Geo-Information 14, no. 12: 461.
https://doi.org/10.3390/ijgi14120461
APA Style
Lyu, Y., Tang, Z., Li, Y., Liu, B., Deng, M., & Wu, G.
(2025). A Multi-Agent Deep Reinforcement Learning Method with Diversified Policies for Continuous Location of Express Delivery Stations Under Heterogeneous Scenarios. ISPRS International Journal of Geo-Information, 14(12), 461.
https://doi.org/10.3390/ijgi14120461
