Journal ArticleDOI
Human–Agent Teaming for Multirobot Control: A Review of Human Factors Issues
Reads0
Chats0
TLDR
The human factors literature on intelligent systems was reviewed, and two key human performance issues related to H-A teaming for multirobot control and some promising user interface design solutions to address these issues were discussed.Abstract:
The human factors literature on intelligent systems was reviewed in relation to the following: efficient human supervision of multiple robots, appropriate human trust in the automated systems, maintenance of human operator's situation awareness, individual differences in human-agent (H-A) interaction, and retention of human decision authority. A number of approaches-from flexible automation to autonomous agents-were reviewed, and their advantages and disadvantages were discussed. In addition, two key human performance issues (trust and situation awareness) related to H-A teaming for multirobot control and some promising user interface design solutions to address these issues were discussed. Some major individual differences factors (operator spatial ability, attentional control ability, and gaming experience) were identified that may impact H-A teaming in the context of robotics control.read more
Citations
More filters
Journal ArticleDOI
A Meta-Analysis of Factors Influencing the Development of Trust in Automation: Implications for Understanding Autonomy in Future Systems
TL;DR: This work expands on the previous meta-analytic foundation in the field of human–robot interaction to include all of automation interaction to provide a quantitative representation of factors influencing the development of trust in automation and identify additional areas of needed empirical research.
Journal ArticleDOI
Intelligent Agent Transparency in Human-Agent Teaming for Multi-UxV Management.
Joseph E. Mercado,Michael A. Rupp,Jessie Y. C. Chen,Michael J. Barnes,Daniel Barber,Katelyn Procci +5 more
TL;DR: The results support the benefits of transparency for performance effectiveness without additional costs and will facilitate the implementation of IAs in military settings and will provide useful data to the design of heterogeneous UxV teams.
Journal ArticleDOI
Seven HCI Grand Challenges
Constantine Stephanidis,Gavriel Salvendy,Margherita Antona,Jessie Y. C. Chen,Jianming Dong,Vincent G. Duffy,Xiaowen Fang,Cali M. Fidopiastis,Gino Fragomeni,Limin Paul Fu,Yinni Guo,Don Harris,Andri Ioannou,Kyeong-Ah Jeong,Shin'ichi Konomi,Heidi Krömker,Masaaki Kurosu,James R. Lewis,Aaron Marcus,Gabriele Meiselwitz,Abbas Moallem,Hirohiko Mori,Fiona Fui-Hoon Nah,Stavroula Ntoa,Pei-Luen Patrick Rau,Dylan Schmorrow,Keng Siau,Norbert A. Streitz,Wentao Wang,Sakae Yamamoto,Panayiotis Zaphiris,Jia Zhou +31 more
TL;DR: The Grand Challenges which arise in the current and emerging landscape of rapid technological evolution towards more intelligent interactive technologies, coupled with increased and widened societal needs, as well as individual and collective expectations that HCI, as a discipline, is called upon to address are investigated.
Journal ArticleDOI
Situation awareness-based agent transparency and human-autonomy teaming effectiveness
Jessie Y. C. Chen,Shan G. Lakhmani,Kimberly Stowers,Anthony R. Selkowitz,Julia L. Wright,Michael J. Barnes +5 more
TL;DR: It is shown that the SAT model continues to be an effective tool for facilitating shared understanding and proper calibration of trust in human–agent teams and an expansion of the model is necessary to support teamwork paradigms, which require bidirectional transparency.
ReportDOI
Situation Awareness-Based Agent Transparency
Jessie Y. C. Chen,Katelyn Procci,Michael W. Boyce,Julia L. Wright,Andre Garcia,Michael J. Barnes +5 more
TL;DR: In this article, the authors show that human operators sometimes question the accuracy and effectiveness of agents actions due to the operators difficulties understanding the state/status of the agent and the rationales behind the behaviors.
References
More filters
Journal ArticleDOI
Regression Shrinkage and Selection via the Lasso
TL;DR: A new method for estimation in linear models called the lasso, which minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients being less than a constant, is proposed.
Journal Article
The magical number seven, plus or minus two: some limits on our capacity for processing information
TL;DR: The theory of information as discussed by the authors provides a yardstick for calibrating our stimulus materials and for measuring the performance of our subjects and provides a quantitative way of getting at some of these questions.
Book
The Elements of Statistical Learning: Data Mining, Inference, and Prediction
TL;DR: In this paper, the authors describe the important ideas in these areas in a common conceptual framework, and the emphasis is on concepts rather than mathematics, with a liberal use of color graphics.
Book
The magical number seven plus or minus two: some limits on our capacity for processing information
TL;DR: The theory provides us with a yardstick for calibrating the authors' stimulus materials and for measuring the performance of their subjects, and the concepts and measures provided by the theory provide a quantitative way of getting at some of these questions.
Journal ArticleDOI
An Integrative Model Of Organizational Trust
TL;DR: In this paper, a definition of trust and a model of its antecedents and outcomes are presented, which integrate research from multiple disciplines and differentiate trust from similar constructs, and several research propositions based on the model are presented.