In November 2005, more than thirty people – most of them designer students from ECAL (Ecole Cantonale d’Art de Lausanne) – joined me in Lausanne to take on the following challenge: to satisfy the whims of a curious robot. Our ultimate goal was to build a playroom where a robot could engage in various new learning activities.

Combining the forces of different disciplines often leads to surprising results, and this is proven again during the workshop on the robot's playroom. Because innovation always seems to originate from at least two known things, the convergence of different perspectives on the same subject is essential.

Children, especially young infants, often decide for themselves what they are interested in. They are not forced by someone to learn how to interact with their environment, nor are they constantly being instructed on how to do something. They are not passive learners, but actors of their own development. Most machine learning experiments so far are quite different because a closed set of example data is prepared and the experimenter chooses the algorithm and sets its parameters carefully. For me, the questions are then: Is it possible to build a machine that permanently develops new skills over a long period of time, similar to the way in which children do so? Can a machine learn its own ecology of complex know-how, without a programmer pre-specifying it?