Introducing Real Variables and Integer Objective Functions to Answer Set Programming

被引：1

作者：

Liu, Guohua ^{[1
]}

Janhunen, Tomi ^{[1
]}

Niemela, Ilkka ^{[1
]}

机构：

[1] Aalto Univ, Dept Informat & Comp Sci, HIIT, FI-00076 Aalto, Finland

来源：

DECLARATIVE PROGRAMMING AND KNOWLEDGE MANAGEMENT | 2014年 / 8439卷

关键词：

STABLE MODEL SEMANTICS; CONSTRAINT;

D O I：

10.1007/978-3-319-08909-6_8

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Answer set programming languages have been extended to support linear constraints and objective functions. However, the variables allowed in the constraints and functions are restricted to integer and Boolean domains, respectively. In this paper, we generalize the domain of linear constraints to real numbers and that of objective functions to integers. Since these extensions are based on a translation from logic programs to mixed integer programs, we compare the translation-based answer set programming approach with the native mixed integer programming approach using a number of benchmark problems.

引用

页码：118 / 135

页数：18

共 18 条

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