Automatic Generation of Smart Human-Machine Interfaces

These last years have seen a rapid growth of applications able to interact with humans in a sophisticated way: mood interpretation and adaptation is the next research frontier and it gets closer day by day. This paper introduces a model-driven process able to automate the creation of modern Human-Machine Interfaces. In particular, by proposing a probabilistic extension of Dynamic State Machines, this paper explores the usage of such a formalism in the automatic generation of applications able to understand the mood of the user and to react at the best. The approach is applied to an example case study.