Page 142 - Designing Sociable Robots

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The Motivation System 123

At time step t = 215, the plot shows what happens if a human continues to interact
with the robot despite its “fatigued” state. The robot cannot “fall asleep” as long as the
play-with-toy behavior wins the competition and inhibits the sleep behavior. If the
fatigue-drive exceeds threshold and the robot cannot fall asleep, the robot begins to
show signs of frustration. Eventually the robot’s “frustration” increases until the robot
achieves anger (at t = 1800). Still the human persists with the interaction. Eventually the
robot’s fatigue-level reaches near maximum, and the sleep behavior wins out.
These experiments illustrate a few of the emotive responses of table 8.1 that arise when
engaging a human. It demonstrates how the robot’s emotive cues can be used to regulate
the nature and intensity of the interaction, and how the nature of the interaction influences
the robot’s behavior. (Additional video demonstrations can be viewed on the included
CD-ROM.) The result is an ongoing “dance” between robot and human aimed at main-
taining the robot’s drives within homeostatic bounds and maintaining a good affective
state. If the robot and human are good partners, the robot remains “interested” most of
the time. These expressions indicate that the interaction is of appropriate intensity for the
robot.

8.5 Limitations and Extensions

Kismet’s motivation system appears adequate for generating infant-like social exchanges
with a human caregiver. To incorporate social learning, or to explore socio-emotional de-
velopment, a number of extensions could be made.
Extension to drives To support social learning, new drives could be incorporated into
the system. For instance, a self-stimulation drive could motivate the robot to play by itself,
perhaps modulating its vocalizations to learn how to control its voice to achieve specific
auditory effects. A mastery/curiosity drive might motivate the robot to balance exploration
versus exploitation when learning new skills. This would correlate to the amount of novelty
the robot experiences over time. If its environment is too predictable, this drive could bias
the robot to prefer novel situations. If the environment is highly unpredictable for the robot,
it could show distress, which would encourage the caregiver to slow down.
Ultimately, the drives should provide the robot with a reinforcement signal as Blumberg
(1996) has done. This could be used to motivate the robot to learn communication skills that
satisfy its drives. For instance, the robot may discover that making a particular vocalization
results in having a toy appear. This has the additional effect that the stimulation-drive
becomes satiated. Over time, through repeated games with the caregiver, the caregiver
could treat that particular vocalization as a request for a specific toy. Given enough of these
consistent, contingent interactions during play, the robot may learn to utter that vocalization