Title
Intelligent Agent Transparency in Human-Agent Teaming for Multi-UxV Management.
Abstract
Objective: We investigated the effects of level of agent transparency on operator performance, trust, and workload in a context of human-agent teaming for multirobot management. Background: Participants played the role of a heterogeneous unmanned vehicle (UxV) operator and were instructed to complete various missions by giving orders to UxVs through a computer interface. An intelligent agent (IA) assisted the participant by recommending two plansa top recommendation and a secondary recommendationfor every mission. Method: A within-subjects design with three levels of agent transparency was employed in the present experiment. There were eight missions in each of three experimental blocks, grouped by level of transparency. During each experimental block, the IA was incorrect three out of eight times due to external information (e.g., commander's intent and intelligence). Operator performance, trust, workload, and usability data were collected. Results: Results indicate that operator performance, trust, and perceived usability increased as a function of transparency level. Subjective and objective workload data indicate that participants' workload did not increase as a function of transparency. Furthermore, response time did not increase as a function of transparency. Conclusion: Unlike previous research, which showed that increased transparency resulted in increased performance and trust calibration at the cost of greater workload and longer response time, our results support the benefits of transparency for performance effectiveness without additional costs. Application: The current results will facilitate the implementation of IAs in military settings and will provide useful data to the design of heterogeneous UxV teams.
Year
DOI
Venue
2016
10.1177/0018720815621206
HUMAN FACTORS
Keywords
Field
DocType
intelligent agent transparency,human-agent teaming,multi-UxV management
Transparency (graphic),Intelligent agent,Computer science,Simulation,Workload,Usability,Automation,Human–computer interaction,Artificial intelligence,Operator (computer programming),Robotics,Interface (computing)
Journal
Volume
Issue
ISSN
58
3
0018-7208
Citations 
PageRank 
References 
29
1.24
13
Authors
6
Name
Order
Citations
PageRank
Joseph E. Mercado1291.24
Michael A. Rupp2343.36
Jessie Y. C. Chen323713.86
Michael Barnes49610.31
Daniel Barber5519.73
Katelyn Procci6463.21