Design and Experimental Validation of Transparent Behavior for a Workload-Adaptive Cognitive Agent
This work describes and validates a concept of transparent behavior for adaptive automation in the field of military helicopter missions. The adaptive automation is implemented as a cognitive agent, to serve as an artificial co-pilot. It dynamically adjusts its level of assistance by choosing from different workload-adapted strategies of assistive intervention. However, adaptive interventions may entail a possible drawback. It might be difficult for the human operator to build up a sufficient and stable mental model of the interaction. For the purpose of creating transparent behavior, this contribution provides an approach for the agent to communicate in a more human-like fashion. To quantify the impacts of the additional transparency information the artificial agent communicated, we conducted a human-in-the-loop experiment. The results revealed an enhancement of situation awareness and an increase of perceivable intelligence and other human-like characteristics of the cognitive agent.
KeywordsAdaptive automation Transparency Human factors Situation awareness Trust in automation SAT model Human-Agent teaming
- 3.Brand, Y., Schulte, A.: Model-based prediction of workload for adaptive associate systems. In: Proceedings of the 2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017, pp. 1722–1727 (2017)Google Scholar
- 5.Chen, J.Y.C., Lakhmani, S.G., Stowers, K., Selkowitz, A., Wright, J.L., Barnes, M.J.: Situation awareness-based agent transparency and human-autonomy teaming effectiveness. Theor. Issues Ergon. Sci. (in press)Google Scholar
- 6.Honecker, F., Brand, Y., Schulte, A.: A Task-centered approach for workload-adaptive pilot associate systems. In: Proceedings of the 32nd Conference of the European Association for Aviation Psychology, Cascais (2016)Google Scholar
- 7.Cohen, J., Cohen, P., West, S.G., Aiken, L.S.: Statistical power analysis for the behavioral sciences (1988)Google Scholar
- 8.Lakhmani, S.G., Selkowitz, A., Chen, J.Y.C.: Agent transparency for an autonomous squad member: uncertainty and projected outcomes (ARL Technical report). Aberdeen Proving Ground. U.S. Army Research Laboratory, MD (in preparation)Google Scholar