Toward Energy-Efficient Routing of Multiple AGVs with Multi-Agent Reinforcement Learning

This paper presents a multi-agent reinforcement learning (MARL) algorithm to address the scheduling and routing problems of multiple automated guided vehicles (AGVs), with the goal of minimizing overall energy consumption. The proposed algorithm is developed based on the multi-agent deep determinist...

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Detalles Bibliográficos
Autores principales: Ye, Xianfeng, Deng, Zhiyun, Shi, Yanjun, Shen, Weiming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10301467/
https://www.ncbi.nlm.nih.gov/pubmed/37420781
http://dx.doi.org/10.3390/s23125615

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10301467/
https://www.ncbi.nlm.nih.gov/pubmed/37420781
http://dx.doi.org/10.3390/s23125615

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