Understanding infant development is one of the greatest scientific challenges
of contemporary science. A large source of difficulty comes from the fact that
the development of skills in infants results from the interactions of multiple
mechanisms at multiple spatio-temporal scales. The concepts of "innate" or
"acquired" are not any more adequate tools for explanations, which call for a
shift from reductionist to systemic accounts. To address this challenge,
building and experimenting with robots modeling the growing infant brain and
body is crucial. Systemic explanations of pattern formation in sensorimotor,
cognitive and social development, viewed as a complex dynamical system, require
the use of formal models based on mathematics, algorithms and robots.
Formulating hypothesis about development using such models, and exploring them
through experiments, allows us to consider in detail the interaction between
many mechanisms and parameters. This complements traditional experimental
methods in psychology and neuroscience where only a few variables can be
studied at the same time. Furthermore, the use of robots is of particular
importance. The laws of physics generate everywhere around us spontaneous
patterns in the inorganic world. They also strongly impact the living, and in
particular constrain and guide infant development through the properties of its
(changing) body in interaction with the physical environment. Being able to
consider the body as an experimental variable, something that can be
systematically changed in order to study the impact on skill formation, has
been a dream to many developmental scientists. This is today becoming possible
with developmental robotics