In our own work, we pursue an experimental approach in two highly uncertain, dynamic, and high-dimensional domains: multi-robot learning, and learning by imitation. Both force us to deal with perceptual and action uncertainty, non-stationarity, and real-t
The basis behavior set of a system provides
elements that are not further reducible to each other and that, when
composed by sequential or concurrent execution, produce the complete
behavior repertoire for the system.
Such basis behaviors are
constructed, learned, or evolved from stable, robust interaction
dynamics between the agent/robot and its environment, and serve as a
substrate for the system's more complex behaviors.
My work generalized the notion of basis behaviors to multi-robot
interactions, and demonstrated how a small set of basis behaviors per
robot can be used to demonstrate a rich repertoire of individual and
group-level behaviors, including following, flocking, homing, herding,
aggregation, dispersion, and formations.
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