Qualitative Trees Applied to Bicycle Riding

We present a method for learning qualitative constraint trees implemented in the program QUIN (qualitative induction). At difference with usual decision trees, the leaves of qualitative trees contain qualitative functional constraints as used in qualitative reasoning. We demonstrate the use of qualitative trees by their application to the difficult task of cloning the human skill of bicycle riding. The approach results in qualitative controllers that are straightforward to explain, and also enable optimization of corresponding quantitative controllers which carry out the task in the style similar to the human, but more effectively.