Motion categorisation: Representing velocity qualitatively

被引:3
|
作者
Arrufi, Juan Purcalla [1 ]
Kirsch, Alexandra [1 ]
机构
[1] Univ Tubingen, HCI Chair, Sand 14, D-72076 Tubingen, Germany
关键词
TRAJECTORY CALCULUS; MOVING-OBJECTS;
D O I
10.1016/j.cogsys.2018.06.005
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Categorising is arguably one of the first steps in cognition, because it enables high-level cognitive processing. For a similar reason, categorising is a first step-a preprocessing step-in artificial intelligence, specifically in decision-making, reasoning, and natural language processing. In this paper we categorise the motion of entities. Such categorisations, also known as qualitative representations, represent the preprocessing step for navigation problems with dynamical obstacles. As a central result, we present a general method to generate categorisations of motion based on categorisations of space. We assess its general validity by generating two categorisations of motion from two different spatial categorisations. We show examples of how the categorisations of motion describe and control trajectories. We also establish its soundness in cognitive and mathematical principles. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:117 / 131
页数:15
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