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An Agent-based Architecture for AI-Enhanced Automated Testing for XR Systems, a Short Paper

Authors :
Samira Shirzadehhajimahmood
Saba Gholizadeh Ansari
Rui Prada
Pedro M. Fernandes
I. S. W. B. Prasetya
Source :
ICST Workshops
Publication Year :
2021
Publisher :
arXiv, 2021.

Abstract

This short paper presents an architectural overview of an agent-based framework called iv4XR for automated testing that is currently under development by an H2020 project with the same name. The framework's intended main use case of is testing the family of Extended Reality (XR) based systems (e.g. 3D games, VR sytems, AR systems), though the approach can indeed be adapted to target other types of interactive systems. The framework is unique in that it is an agent-based system. Agents are inherently reactive, and therefore are arguably a natural match to deal with interactive systems. Moreover, it is also a natural vessel for mounting and combining different AI capabilities, e.g. reasoning, navigation, and learning.

Details

Database :
OpenAIRE
Journal :
ICST Workshops
Accession number :
edsair.doi.dedup.....b8c8e1d33e5a07a1412623688d55082c
Full Text :
https://doi.org/10.48550/arxiv.2104.06132