图 书 馆
利用受限强化学习优化债务催收Optimizing Debt Collections Using Constrained Reinforcement Learning |
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| 课程网址: | http://videolectures.net/kdd2010_abe_odcucrl/ |
| 主讲教师: | Naoki Abe |
| 开课单位: | IBM公司 |
| 开课时间: | 2010-10-01 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | The problem of optimally managing the collections process by taxation authorities is one of prime importance, not only for the revenue it brings but also as a means to administer a fair taxing system. The analogous problem of debt collections management in the private sector, such as banks and credit card companies, is also increasingly gaining attention. With the recent successes in the applications of data analytics and optimization to various business areas, the question arises to what extent such collections processes can be improved by use of leading edge data modeling and optimization techniques. In this paper, we propose and develop a novel approach to this problem based on the framework of constrained Markov Decision Process (MDP), and report on our experience in an actual deployment of a tax collections optimization system at New York State Department of Taxation and Finance (NYS DTF). |
| 关 键 词: | 税务机关; 优化管理; 私营部门 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-04-30：chenxin |
| 阅读次数: | 35 |