Integrating situated human interaction modeling and stochastic state automata for improved technical situation awareness

Abstract

In this contribution, a combination of two methods for the evaluation of the best behavior including situated decisions based on the assessment of human actions or decisions related to actions is presented. The suggestion of the behavior is based on a Situation-OperatorModeling approach in combination with a stochastic state machine. While the SituationOperator-Modeling (SOM) allows the concrete, individualized, and situated modeling of human interaction in formal context, an approach is used to work with a stochastic state automata. First based on observations (training), the observed transition probability between predefined states. The combination of both practical and theoretical approaches allows the combined prediction of human behavior.