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Intelligent Action | Synapse

February 28, 2026Open Access

Intelligent Action

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Key Points

The aim is to develop a dynamical model for understanding action via the Reasoning Turing Machine framework.
Developed a dynamical formulation of action
Modeled action as force equilibrium in an epistemic manifold
Derived a continuous-time law of behavior formation
Analyzed stability and admissibility conditions from a nonlinear dynamical systems perspective.
Demonstrated that coherent action arises from internal force balance
Showed that behavior formation does not rely on reward maximization
Introduced new insights into stability properties of action formation.

Abstract

This paper develops a dynamical formulation of action within the Reasoning Turing Machine (RTM) framework. Action is modeled as the result of force equilibrium in an epistemic manifold, where multiple structured drives interact under behavioral gating. A continuous-time law of behavior formation is derived, showing how coherent action emerges from internal force balance rather than reward maximization. Stability properties and admissibility conditions are analyzed within a nonlinear dynamical systems perspective.

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Authors

A

Alireza Khajouei

M

Mehdi Sabzalian

Actions

Institutions

Department for Work and Pensions

References and Citations

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Cite this study

Khajouei et al. (Thu,) studied this question.

synapsesocial.com/papers/69a287e20a974eb0d3c03a9e — DOI: https://doi.org/10.5281/zenodo.18793095