ArticleProceedings of the National Academy of Sciences of the United States of America2019
Human social motor solutions for human-machine interaction in dynamical task contexts.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- Gaze facilitates responsivity during hand coordinated joint attention.Scientific reports · 2021Trial
- Successful coordination emerges from aligned self-predictions in a dynamic motor interaction.Communications psychology · 2026Article
- Abduction and Deduction in Dynamical Cognitive Science.Topics in cognitive science · 2026Review
- Human-AI collaboration: trade-offs between performance and preferences.Cognitive research: principles and implications · 2026Article
- Addressing loneliness by AI chatbot: a qualitative study of empty-nest elderly.BMC public health · 2026Article
- Dynamic neural processing of self-other synchronization error in interpersonal coordination.iScience · 2025Article
- Nonreciprocal field theory for decision-making in multi-agent control systems.Nature communications · 2025Article
- Discovering Dynamical Laws for Speech Gestures.Cognitive science · 2025Article
- Interdependent minds: Quantifying the dynamics of successful social interaction.Current directions in psychological science · 2025Article
- Human-inspired strategies for controlling swarm systems.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025Review
- Modelling human navigation and decision dynamics in a first-person herding task.Royal Society open science · 2024Article
- Interpersonal strategy for controlling unpredictable opponents in soft tennis.Scientific reports · 2024Article
- Autistic young people adaptively use gaze to facilitate joint attention during multi-gestural dyadic interactions.Autism : the international journal of research and practice · 2024Article
- Dyadic body competence predicts movement synchrony during the mirror game.Frontiers in human neuroscience · 2024Article
- (Mis)align: a simple dynamic framework for modeling interpersonal coordination.Scientific reports · 2023Article
- Predicting and understanding human action decisions during skillful joint-action using supervised machine learning and explainable-AI.Scientific reports · 2023Article
- Assessing Team Effectiveness by How Players Structure Their Search in a First-Person Multiplayer Video Game.Cognitive science · 2022Article
- Synchrony in triadic jumping performance under the constraints of virtual reality.Scientific reports · 2022Article
- Assessing attentive monitoring levels in dynamic environments through visual neuro-assisted approach.Heliyon · 2022Article
- Conversation dynamics in a multiplayer video game with knowledge asymmetry.Frontiers in psychology · 2022Article
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Authors and funding
7 authors.
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Abstract
Multiagent activity is commonplace in everyday life and can improve the behavioral efficiency of task performance and learning. Thus, augmenting social contexts with the use of interactive virtual and robotic agents is of great interest across health, sport, and industry domains. However, the effectiveness of human-machine interaction (HMI) to effectively train humans for future social encounters depends on the ability of artificial agents to respond to human coactors in a natural, human-like manner. One way to achieve effective HMI is by developing dynamical models utilizing dynamical motor primitives (DMPs) of human multiagent coordination that not only capture the behavioral dynamics of successful human performance but also, provide a tractable control architecture for computerized agents. Previous research has demonstrated how DMPs can successfully capture human-like dynamics of simple nonsocial, single-actor movements. However, it is unclear whether DMPs can be used to model more complex multiagent task scenarios. This study tested this human-centered approach to HMI using a complex dyadic shepherding task, in which pairs of coacting agents had to work together to corral and contain small herds of virtual sheep. Human-human and human-artificial agent dyads were tested across two different task contexts. The results revealed (
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.