A Dynamical Framework for Cognitive Processes Based on Transformations and Semantic Equivalence
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arXiv:2605.23942v1 Announce Type: new Abstract: This paper proposes a structural and dynamical framework for modeling cognitive processes within a cybernetic perspective. Cognitive states are represented as elements of a state space evolving through an iterative update rule of the form \[ X_{t+1} = \pi\big(F(f(X_t))\big), \] where $f$ describes internal transformations, $F$ represents interpretative mappings, and $\pi$ enforces semantic equivalence. The model is interpreted as a feedback system
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✦ AI Summary· Claude Sonnet
Computer Science > Artificial Intelligence
[Submitted on 29 Apr 2026]
A Dynamical Framework for Cognitive Processes Based on Transformations and Semantic Equivalence
Carlo Cattani, Dioneia Motta Monte-Serrat
This paper proposes a structural and dynamical framework for modeling cognitive processes within a cybernetic perspective. Cognitive states are represented as elements of a state space evolving through an iterative update rule of the form
X_{t+1} = \pi\big(F(f(X_t))\big),
where f describes internal transformations, F represents interpretative mappings, and \pi enforces semantic equivalence.
The model is interpreted as a feedback system integrating transformation, observation, and stabilization. A categorical formulation is introduced to capture compositional structure, while the associated dynamics are analyzed through fixed-point arguments and contraction conditions ensuring stability.
To demonstrate the operational character of the framework, a computational illustration is provided, together with a qualitative analysis of the induced dynamics. A concrete linguistic application shows how context-dependent interpretation can be modeled as a trajectory toward a stable semantic class.
The proposed approach connects dynamical systems, category theory, and cognitive modeling, and provides a unified representation of cognition as a feedback-driven process evolving toward invariant interpretations.
Subjects: Artificial Intelligence (cs.AI)
Cite as: arXiv:2605.23942 [cs.AI]
(or arXiv:2605.23942v1 [cs.AI] for this version)
https://doi.org/10.48550/arXiv.2605.23942
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Submission history
From: Carlo Cattani [view email]
[v1] Wed, 29 Apr 2026 16:56:52 UTC (24 KB)
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