标题:CRSRL: Customer routing system using reinforcement learning
作者:C., Long; Z., Liu; X., Lu; Z., Hu; Y., Wang
作者机构:[2;2;2;2;2] Ant Financial Services Group, Z Space No. 556 Xixi Road, Hangzhou, Zhejiang; 310099, China;[] RMIT University, GPO Box 2476, Melbourne; VI 更多
会议名称:28th International Joint Conference on Artificial Intelligence, IJCAI 2019
会议日期:10 August 2019 through 16 August 2019
来源:IJCAI International Joint Conference on Artificial Intelligence
出版年:2019
卷:2019-August
页码:6548-6550
摘要:Allocating resources to customers in the customer service is a difficult problem, because designing an optimal strategy to achieve an optimal trade-off between available resources and customers' satisfaction is non-trivial. In this paper, we formalize the customer routing problem, and propose a novel framework based on deep reinforcement learning (RL) to address this problem. To make it more practical, a demo is provided to show and compare different models, which visualizes all decision process, and in particular, the system shows how the optimal strategy is reached. Besides, our demo system also ships with a variety of models that users can choose based on their needs. © 2019 International Joint Conferences on Artificial Intelligence. All rights reserved.
收录类别:EI;SCOPUS
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074948565&partnerID=40&md5=71f0ba98ec1031e96bb3dfa95730fd9c
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