Qualitative Reasoning about 2D Cardinal Directions using Answer Set Programming

被引:0
|
作者
Izmirlioglu, Yusuf [1 ]
Erdem, Esra [2 ]
机构
[1] New Mexico State Univ, Dept Comp Sci, Las Cruces, NM 88003 USA
[2] Sabanci Univ, Fac Engn & Nat Sci, TR-34956 Istanbul, Turkiye
关键词
EXTENDED OBJECTS; ORIENTATION; DISTANCE; INFORMATION; KNOWLEDGE;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We introduce a formal framework (called NCDC-ASP ) for representing and reasoning about cardinal directions between extended spatial objects on a plane, using Answer Set Programming (ASP). NCDC-ASP preserves the meaning of cardinal directional relations as in Cardinal Direc-tional Calculus (CDC), and provides solutions to all consistency checking problems in CDC under various conditions (i.e., for a complete/incomplete set of basic/disjunctive CDC constraints over connected/disconnected spatial objects). In particular, NCDC-ASP models a discretized version of the consistency checking problem in ASP, over a finite grid (rather than a plane), where we provide new lower bounds on the grid size to guarantee that it correctly characterizes solutions for the consistency checking in CDC. In addition, NCDC-ASP has the following two novelties im-portant for applications. NCDC-ASP introduces default CDC constraints to represent and reason about background or commonsense knowledge that involves default qualitative directional rela-tions (e.g., "the ice cream truck is by default to the north of the playground" or "the keyboard is normally placed in front of the monitor"). NCDC-ASP introduces inferred CDC constraints to allow inference of missing CDC relations and to provide them as explanations. We illustrate the uses and usefulness of NCDC-ASP with interesting scenarios from the real-world. We design and develop a variety of benchmark instances, and comprehensively evaluate NCDC-ASP from the perspectives of computational efficiency.
引用
收藏
页码:1371 / 1453
页数:83
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