Behavioral Attractors: Typed Inertia and an Option Generator as a Structural Framework for Behavior Change
Year: 2026
Type: preprint
Abstract: This work proposes Capture Dynamics (part of the Theory of Variability, ToV), a structural framework for behavior change. In it, behavior is a position in a state space; an attractor is the configuration in which the system is energetically and cognitively cheapest to maintain; inertia is the restoring force back to that configuration; and the set of options a person can even conceive and choose is produced by a generator G from the current state, forming the option space Ω(Sₜ). The framework departs from holistic attractor models in three ways: the state is decomposed into layers, each with its own inertia and return regime; an explicit generator G is introduced, with output Ω; and the depth of an intervention is typed separately from its content (levels 1-5). It also adds cross-layer coupling between attractors and an energy gate E(Sₜ), which specifies the condition under which no stable transition is available until the prevailing constraints themselves change.The aim of the paper is to set out the conceptual apparatus of the framework, show its relation to existing attractor models, formulate the falsifiable predictions that follow from it, and draw an explicit line between what is already supported in the literature and what ToV posits and leaves to empirical test. The paper is theoretical: it reports no new empirical results but offers a structural framework and a program for obtaining them.English translation of the preprint. The Russian original is available at https://doi.org/10.5281/zenodo.20730164
Author: Ryzhkova, Julia
Language: English
Subfield: Applied Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7165027426
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