Equipping robots with complex capabilities still requires a great amount of effort. In this
work a novel approach is proposed to understand to represent and to execute object
manipulation tasks learned from observation by combining methods of data analysis graphical
modeling and artificial intelligence. Employing this approach enables robots to reason about
how to solve tasks in dynamic environments and to adapt to unseen situations.
