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Attention Guidance Agents with Eye-Tracking

A Use-Case Based on the MATBII Cockpit Task

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Engineering Multi-Agent Systems (EMAS 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13190))

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Abstract

A first step to keeping the human ‘in the loop’ in the context of developing intelligent multi-task interfaces is to be able to monitor their attention. By combining eye tracking with agent monitoring and decision making, we provide a basis for increasing the user’s attentional bandwidth by offering bottom-up attention guidance. We develop a modified implementation of the MATBII cockpit task simulator embedded in an agent environment in which agents monitor events, including eye tracking, and act to deploy visual cues to guide attention. We explore how such a system may be useful for improving task performance, by also simulating users with agents to demonstrate how the system might work for some examples of user behaviour. We also discuss how our system can act as an experimental platform to benefit future user experience research focusing on attention guidance in complex multi-task interfaces.

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Notes

  1. 1.

    https://dicelab-rhul.github.io/ICU/.

  2. 2.

    https://dicelab-rhul.github.io/ICU/documentation/configuration/.

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Acknowledgements

The work for developing this demonstrator was supported by a Human-Like Computing EPSRC Network+ Kickstart grant. Thanks to Suzy Broadbent and Lisa Boyce for discussions and support.

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Correspondence to Szonya Durant .

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Durant, S., Wilkins, B., Woods, C., Uliana, E., Stathis, K. (2022). Attention Guidance Agents with Eye-Tracking. In: Alechina, N., Baldoni, M., Logan, B. (eds) Engineering Multi-Agent Systems. EMAS 2021. Lecture Notes in Computer Science(), vol 13190. Springer, Cham. https://doi.org/10.1007/978-3-030-97457-2_6

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