Using Boolean Functions of Context Factors for Adaptive Mental Model Aggregation in Organisational Learning

Aggregation of individual mental models to obtain shared for an organization is a crucial process organizational learning. This aggregation usually depends on several context factors that may vary over circumstances. It explored how Boolean functions these can be used model this form adaptation. For adaptation connections (represented by first-order self-model states), second-order adaptive self-modeling network learning was designed. shown in such model, express logical combinations and based exert context-sensitive control the process.