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  1. Prospects for Augmenting Team Interactions with Real‐Time Coordination‐Based Measures in Human‐Autonomy Teams.Travis J. Wiltshire,Kyana van Eijndhoven,Elwira Halgas &Josette M. P. Gevers -2024 -Topics in Cognitive Science 16 (3):391-429.
    Complex work in teams requires coordination across team members and their technology as well as the ability to change and adapt over time to achieve effective performance. To support such complex interactions, recent efforts have worked toward the design of adaptive human-autonomy teaming systems that can provide feedback in or near real time to achieve the desired individual or team results. However, while significant advancements have been made to better model and understand the dynamics of team interaction and its relationship (...) with task performance, appropriate measures of team coordination and computational methods to detect changes in coordination have not yet been widely investigated. Having the capacity to measure coordination in real time is quite promising as it provides the opportunity to provide adaptive feedback that may influence and regulate teams’ coordination patterns and, ultimately, drive effective team performance. A critical requirement to reach this potential is having the theoretical and empirical foundation from which to do so. Therefore, the first goal of the paper is to review approaches to coordination dynamics, identify current research gaps, and draw insights from other areas, such as social interaction, relationship science, and psychotherapy. The second goal is to collate extant work on feedback and advance ideas for adaptive feedback systems that have potential to influence coordination in a way that can enhance the effectiveness of team interactions. In addressing these two goals, this work lays the foundation as well as plans for the future of human-autonomy teams that augment team interactions using coordination-based measures. (shrink)
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  • Attentional coordination in demonstrator-observer dyads facilitates learning and predicts performance in a novel manual task.Murillo Pagnotta,Kevin N. Laland &Moreno I. Coco -2020 -Cognition 201 (C):104314.
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  • Assessing Team Effectiveness by How Players Structure Their Search in a First‐Person Multiplayer Video Game.Patrick Nalepka,Matthew Prants,Hamish Stening,James Simpson,Rachel W. Kallen,Mark Dras,Erik D. Reichle,Simon G. Hosking,Christopher Best &Michael J. Richardson -2022 -Cognitive Science 46 (10):e13204.
    Cognitive Science, Volume 46, Issue 10, October 2022.
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  • Editor's Introduction and Review: Coordination and Context in Cognitive Science.Christopher T. Kello -2018 -Topics in Cognitive Science 10 (1):6-17.
    The literature on coordination within and between individuals is reviewed, with an emphasis on the inherent transience of coordination patterns in behavioral activity. This transience is integral to understanding cognitive activity as flexible patterns of coordination in brain, body, and environment. Kello reviews the articles in this special issue as contributions to understanding the role of context in shaping or interpreting coordination patterns in human behavior.
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  • Great Minds Think Alike? Spatial Search Processes Can Be More Idiosyncratic When Guided by More Accurate Information.Michal Król &Magdalena E. Król -2022 -Cognitive Science 46 (4).
    Cognitive Science, Volume 46, Issue 4, April 2022.
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  • Do You Follow?: A Fully Automated System for Adaptive Robot Presenters.Agnes Axelsson &Gabriel Skantze -2023 -Hri '23: Proceedings of the 2023 Acm/Ieee International Conference on Human-Robot Interaction 23:102-111.
    An interesting application for social robots is to act as a presenter, for example as a museum guide. In this paper, we present a fully automated system architecture for building adaptive presentations for embodied agents. The presentation is generated from a knowledge graph, which is also used to track the grounding state of information, based on multimodal feedback from the user. We introduce a novel way to use large-scale language models (GPT-3 in our case) to lexicalise arbitrary knowledge graph triples, (...) greatly simplifying the design of this aspect of the system. We also present an evaluation where 43 participants interacted with the system. The results show that users prefer the adaptive system and consider it more human-like and flexible than a static version of the same system, but only partial results are seen in their learning of the facts presented by the robot. (shrink)
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