Contemporary cognitive science actively employs probabilistic models of thought, including Bayesian approaches and predictive processing theory. These models successfully describe the updating of hypothesis probabilities and decision-making processes. However, most existing theoretical frameworks lack a strictly defined minimal operational unit of meaning formation capable of describing a completed act of cognitive interpretation. This article proposes a theoretical model in which the cognitive process is understood as a sequence of uncertainty-reduction operations within a space of interpretations. It introduces a formal definition of the unit of meaning as the minimal completed cycle of interpretation, including incoming information, a hypothesis space, an act of interpretative selection, and the result of hypothesis testing. The formal structure of the unit of meaning is proposed as follows: S = (I, H, D, R) where: I — input information, H — the set of interpretative hypotheses, D — the act of interpretative selection, R — the result of testing or stabilizing the selected interpretation. It is argued that each such operation reduces the uncertainty of the interpretative space. The accumulation of a sequence of units of meaning forms a system of knowledge. The model is integrated into the author’s theoretical system ICE → Dominanta X → HUMP → IFI, in which Dominanta X performs the function of temporal stabilization of interpretation, while the Interpretative Freedom Index (IFI) determines the efficiency of uncertainty reduction within the cognitive system. The proposed model connects probabilistic theories of cognition, information theory, and the philosophy of knowledge by offering a formalized approach to the analysis of knowledge production in both individual and collective cognitive systems.
Igor Kaminskyi (Sat,) studied this question.