两篇新研究论文探讨了深度强化学习（DRL）在不同情境下优化电池管理的应用。一篇论文详细介绍了一个用于爱尔兰奶牛场的多智能体DRL系统，旨在通过优化电池用于能源套利来提高可再生能源整合并减少排放，显示出高达18%的潜在利润增长。另一篇论文则关注仓库中自主移动机器人的动态电池管理，使用近端策略优化（PPO）将订单完成率提高高达6%，并减少充电时间。 AI
影响 展示了先进的AI技术在不同实际应用中优化能源管理和运营效率。
排序理由 两篇发表在arXiv上的学术论文，详细介绍了深度强化学习的新颖应用。
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arXiv:2607.06489v1 Announce Type: new Abstract: The dairy industry in Ireland has a large potential for the integration of renewable energy and the reduction of carbon emissions. However, researchers of distributed generation control are mainly focused on residential and commerci…
arXiv:2607.05683v1 Announce Type: new Abstract: Battery charging of Autonomous Mobile Robots (AMRs) in warehouses is a critical operational challenge that heavily impacts both order processing times and throughput. In this study, we address the dynamic AMR charging problem under …
The dairy industry in Ireland has a large potential for the integration of renewable energy and the reduction of carbon emissions. However, researchers of distributed generation control are mainly focused on residential and commercial applications. To contribute to the effective …
Battery charging of Autonomous Mobile Robots (AMRs) in warehouses is a critical operational challenge that heavily impacts both order processing times and throughput. In this study, we address the dynamic AMR charging problem under stochastic order arrivals, where robots must lea…