| Abstract |
To develop a robot that is able to recognize and show affective behavior, it
should be able to regulate simultaneously occurring tendencies of positive
and negative emotions. To achieve this, the current paper introduces a
computational model for involvement-distance trade-offs, based on an
existing theoretical model. The main mechanisms of this model have been
represented as regression equations, using the LEADSTO modeling environment.
A number of simulation experiments have been performed, which resulted in
two important conclusions. First, the trade-off between involvement and
distance can be modeled adequately using the ‘max’ version of Werners’
fuzzy_AND operator. Second, the experiments confirmed the empirical finding
that positive features do not exclusively increase involvement. |