Towards Explainability for a Civilian UAV Fleet Management using an Agent-based Approach
This addresses the need for explainable AI in UAV fleet management for civilian operators, but it is incremental as it presents an initial design concept without proven results.
The paper tackles the problem of managing civilian UAV fleets by proposing an agent-based simulation system that emphasizes explainability to aid human operators in critical scenarios, with evaluation planned through a human-computer interaction study.
This paper presents an initial design concept and specification of a civilian Unmanned Aerial Vehicle (UAV) management simulation system that focuses on explainability for the human-in-the-loop control of semi-autonomous UAVs. The goal of the system is to facilitate the operator intervention in critical scenarios (e.g. avoid safety issues or financial risks). Explainability is supported via user-friendly abstractions on Belief-Desire-Intention agents. To evaluate the effectiveness of the system, a human-computer interaction study is proposed.