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Infant-like Social Interactions between a Robot and a Human Caregiver

Massachusetts Institute of Technology Artificial Intelligence Lab

Brian Scassellati

Massachusetts Institute of Technology Artificial Intelligence Lab

From birth, human infants are immersed in a social environment that allows them to learn by leveraging the skills and capabilities of their caregivers. A critical pre-cursor to this type of social learning is the ability to maintain interaction levels that are neither overwhelming nor under-stim ulating. In this paper, we present a mechanism for an autonomous robot to regulate the intensity of its social interactions with a human. Similar to the feedback from infant to caregiver, the robot uses expressive displays to modulate the interaction intensity. This mechanism is integrated within a general framework that combines perception, attention, drives, emotions, behavior selection, and motor acts. We present a specific implementation of this architecture that enables the robot to react appropriately to both social stimuli (faces) and non-social stimuli (moving toys) while maintaining a suitable interaction intensity. We present results from both face-to-face interactions and interactions mediated through a toy.

Note: This paper was submitted in June, 1998.

Adaptive Behavior, Vol. 8, No. 1, 49-74 (2000)
DOI: 10.1177/105971230000800104


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