What do we learn about development from baby robots?
This work addresses a foundational problem in developmental science by offering a novel approach to study complex interactions in infant development, though it is incremental in applying robotics to an existing field.
The paper tackles the challenge of understanding infant development by proposing the use of robots to model the growing brain and body, enabling systemic explanations of skill formation through formal models and experiments that consider multiple interacting mechanisms and physical constraints.
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.