ArticlePLoS computational biology2019
Incomplete information about the partner affects the development of collaborative strategies in joint action.
Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Article
- Model predictive game control for personalized and targeted interactive assistance.Communications engineering · 2026Article
- Partner-sourced haptic feedback rather than environmental inputs drives coordination improvement in human dyadic collaboration.Scientific reports · 2025Article
- Analyzing coordinated group behavior through role-sharing: a pilot study in female 3-on-3 basketball with practical application.Frontiers in sports and active living · 2025Article
- Article
- Computational joint action: Dynamical models to understand the development of joint coordination.PLoS computational biology · 2024Article
- Low-force human-human hand interactions induce gait changes through sensorimotor engagement instead of direct mechanical effects.Scientific reports · 2024Article
- Interacting humans use forces in specific frequencies to exchange information by touch.Scientific reports · 2022Article
- Humans utilize sensory evidence of others' intended action to make online decisions.Scientific reports · 2022Article
- Inter-personal motor interaction is facilitated by hand pairing.Scientific reports · 2022Article
- Analysis of group behavior based on sharing heterogeneous roles in a triad using a coordinated drawing task.Frontiers in psychology · 2022Article
- Human-machine-human interaction in motor control and rehabilitation: a review.Journal of neuroengineering and rehabilitation · 2021Review
- Motor Learning in Robot-Based Haptic Dyads: A Review.IEEE transactions on hapticsReview
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Physical interaction with a partner plays an essential role in our life experience and is the basis of many daily activities. When two physically coupled humans have different and partly conflicting goals, they face the challenge of negotiating some type of collaboration. This requires that both participants understand their partner's state and current actions. But, how would the collaboration be affected if information about their partner were unreliable or incomplete? We designed an experiment in which two players (a dyad) are mechanically connected through a virtual spring, but cannot see each other. They were instructed to perform reaching movements with the same start and end position, but through different via-points. In different groups of dyads we varied the amount of information provided to each player about his/her partner: haptic only (the interaction force perceived through the virtual spring), visuo-haptic (the interaction force is also displayed on the screen), and partner visible (in addition to interaction force, partner position is continuously displayed on the screen). We found that incomplete information about the partner affects not only the speed at which collaboration is achieved (less information, slower learning), but also the actual collaboration strategy. In particular, incomplete or unreliable information leads to an interaction strategy characterized by alternating leader-follower roles. Conversely, more reliable information leads to more synchronous behaviors, in which no specific roles can be identified. Simulations based on a combination of game theory and Bayesian estimation suggested that synchronous behaviors correspond to optimal interaction (Nash equilibrium). Roles emerge as sub-optimal forms of interaction, which minimize the need to account for the partner. These findings suggest that collaborative strategies in joint action are shaped by the trade-off between the task requirements and the uncertainty of the information available about the partner.
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Registered trials
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.