Controlling the Average Behavior of Business Rules Programs

被引：4

作者：

Wang, Olivier ^{[1
,2
]}

Liberti, Leo ^{[2
]}

D'Ambrosio, Claudia ^{[2
]}

de Sainte Marie, Christian ^{[1
]}

Ke, Changhai ^{[1
]}

机构：

[1] IBM France, 9 Rue Verdun, F-94250 Gentilly, France

[2] Ecole Polytech, CNRS LIX, F-91128 Palaiseau, France

来源：

RULE TECHNOLOGIES: RESEARCH, TOOLS, AND APPLICATIONS | 2016年 / 9718卷

关键词：

D O I：

10.1007/978-3-319-42019-6_6

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

Business Rules are a programming paradigm for non-programmer business users. They are designed to encode empirical knowledge of a business unit by means of "if-then" constructs. The classic example is that of a bank deciding whether to open a line of credit to a customer, depending on how the customer answers a list of questions. These questions are formulated by bank managers on the basis of the bank strategy and their own experience. Banks often have goals about target percentages of allowed loans. A natural question then arises: can the Business Rules be changed so as to meet that target on average? We tackle the question using "machine learning constrained" mathematical programs, which we solve using standard off-the-shelf solvers. We then generalize this to arbitrary decision problems.

引用

页码：83 / 96

页数：14