Clustering social cues to determine social signals: developing learning algorithms using the "n-most likely states" approach-Reference-Cited by-同舟云学术

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Clustering social cues to determine social signals: developing learning algorithms using the "n-most likely states" approach

Published:2016-05-13 Issue: Volume: Page:
ISSN:0277-786X
Container-title:SPIE Proceedings
language:
Short-container-title:

Author:

Best Andrew,Kapalo Katelynn A.,Warta Samantha F.,Fiore Stephen M.

Publisher

SPIE

Reference50 articles.

1. Robotics

2. The Pransky interview: Dr Paolo Pirjanian, CTO of iRobot Corporation

3. Toward understanding social cues and signals in human-robot interaction: Effects of robot gaze and proxemic behavior;Fiore,2013

4. Army Research Laboratory. Robotics Collaborative Technology Alliance (RCTA) FY 2012 annual program plan. Retrieved from: http://www.arl.army.mil/www/pages/392/RCTA_FY12_APP.pdf, (2012).

5. Leveraging social judgment theory to examine the relationship between social cues and signals in human-robot interactions;Wiltshire,2014

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1. Individual and team profiling to support theory of mind in artificial social intelligence;Scientific Reports;2024-06-02

2. Supporting Social Interactions In Human-Ai Teams: Profiling Human Teammates From Sparse Data;Proceedings of the Human Factors and Ergonomics Society Annual Meeting;2021-09

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