Industrial Applications of Answer Set Programming

被引：54

作者：

Falkner, Andreas ^{[2
]}

Friedrich, Gerhard ^{[1
]}

Schekotihin, Konstantin ^{[1
,2
]}

Taupe, Richard

Teppan, Erich C. ^{[1
]}

机构：

[1] Alpen Adria Univ Klagenfurt, Klagenfurt, Austria

[2] Siemens AG Osterreich, Vienna, Austria

来源：

KUNSTLICHE INTELLIGENZ | 2018年 / 32卷 / 2-3期

关键词：

Answer set programming; Applications;

D O I：

10.1007/s13218-018-0548-6

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Automated problem solving in combination with declarative specifications of search-problems have shown to substantially improve the implementation and maintenance costs as well as the man-machine interaction of deployed industrial applications. The knowledge representation and reasoning (KRR) framework of answer set programming (ASP) offers a rich representation language and high performance solvers. Therefore, ASP has become very attractive for the representation and solving of search-problems both for academia and industry. This article focuses on the latest industrial applications of ASP. We do not only present successful applications of ASP but also describe the development process and the design of ASP programs in an industrial context. Finally, we discuss current approaches to tackle the most significant application challenges such as grounding and runtime improvements by heuristics.

引用

页码：165 / 176

页数：12

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