The RUBI project: a progress report
Proceedings of the ACM/IEEE international conference on Human-robot interaction
An Embodied Cognition Approach to Mindreading Skills for Socially Intelligent Robots
International Journal of Robotics Research
2010 Special Issue: Detecting contingencies: An infomax approach
Neural Networks
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We propose a view of gaze following in which infantsact as Bayesian learners actively attempting to identify theoperating characteristics of the systems with which theyinteract. We present results of an experiment in which 28infants (average age 10 months) interacted for a 3 minuteperiod with a non-humanoid robot.For half the infants therobot simulated contingency structure typically producedby human beings.In particular it provided causal informationabout the existence of a line of regard.For the other 14 infants, the robot behaved in a manner which was not contingent with the environment.We found that a few minutes of interaction with the contingent robot was sufficient to elicit statistically detectable gaze following.There were clear signs that some of these infants were actively attempting to identify whether or not the robot was responsive to them.We propose that the infant brain is equipped to learn and analyze the contingency structure of real-time social interactions. Contingency is a fundamental perceptual dimension used by infants to recognize the operationalproperties of humans and to generalize existing behaviorsto new social partners.