An Agent-based Architecture for AI-Enhanced Automated Testing for XR Systems, a Short Paper
It addresses automated testing challenges for XR systems, but appears incremental as it builds on existing agent-based approaches.
The paper presents an agent-based framework called iv4XR for automated testing of Extended Reality (XR) systems, such as VR and AR, aiming to leverage agents' reactivity and AI capabilities for improved testing.
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.