Reinforcement Learning in Anylogic Simulation Models: A Guiding Example Using Pathmind

Mohammed Farhan, Brett Göhre, Edward Junprung
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引用次数: 7

Abstract

Reinforcement Learning has recently gained a lot of exposure in the simulation industry. In this paper, we demonstrate the use of reinforcement learning in AnyLogic software models using Pathmind. A coffee shop simulation is built to train a barista to make correct operational decisions and improve efficiency that directly affects customer service time. The trained policy outperforms rule-based functions in terms of customer service time and throughput.
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任意逻辑仿真模型中的强化学习:使用路径思维的指导示例
最近,强化学习在仿真行业中得到了很多关注。在本文中,我们演示了使用Pathmind在AnyLogic软件模型中使用强化学习。建立了一个咖啡馆模拟,以培训咖啡师做出正确的运营决策,提高直接影响客户服务时间的效率。经过训练的策略在客户服务时间和吞吐量方面优于基于规则的功能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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