Motion Categorisation: Representing Velocity Qualitatively - Archive ouverte HAL Access content directly
Journal Articles Cognitive Systems Research Year : 2018

Motion Categorisation: Representing Velocity Qualitatively

Abstract

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. And we establish its soundness in cognitive and mathematical principles.
Fichier principal
Vignette du fichier
purcalla18motion-preprint.pdf (688.77 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01845141 , version 1 (20-07-2018)

Identifiers

Cite

Juan Purcalla Arrufi, Alexandra Kirsch. Motion Categorisation: Representing Velocity Qualitatively. Cognitive Systems Research, 2018, 52, pp.117 - 131. ⟨10.1016/j.cogsys.2018.06.005⟩. ⟨hal-01845141⟩
26 View
161 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More