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

Mohammed Farhan, Brett Göhre, Edward Junprung
{"title":"Reinforcement Learning in Anylogic Simulation Models: A Guiding Example Using Pathmind","authors":"Mohammed Farhan, Brett Göhre, Edward Junprung","doi":"10.1109/WSC48552.2020.9383916","DOIUrl":null,"url":null,"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.","PeriodicalId":6692,"journal":{"name":"2020 Winter Simulation Conference (WSC)","volume":"40 1","pages":"3212-3223"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 Winter Simulation Conference (WSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WSC48552.2020.9383916","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.
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。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信