Social scientists have struggled to make sense in the shift between individual and group perception, the difference between observation and action, and the meaning of interdependence.

Two obstacles confront researchers modeling the dynamics of behavior in homogenous or heterogeneous (mixed) groups and organizations composed of humans, ma-
chines or robots: human agent observations, known as self-reports, and interdependent uncertainties in social interaction. To overcome these obstacles to model mixed systems
of human and virtual agents or robots requires a theory encompassing these effects under uncertainty.

Both obstacles are consequence of that, in general, perception is not able to give enough information to consistently decide the engagement in an action. Thus, individuals decide their actions having uncertainty on the information they need to be sure to decide.

It has been shown that uncertainty changes in a non-trivial manner the decision processes. Indeed, no classical logic or classical probabilty approaches are able to model the way humans engage in actions when there is uncertainty on the information. Quantum-logic based approaches have been proven to cope with the problems arising from uncertainty.

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