The Variational Epistemic Inequity-Aversion Framework: An Exploratory Conceptual Synthesis of Active Inference Analogies in Social Networks

This paper introduces an exploratory conceptual synthesis that maps Karl Friston's Free Energy Principle (FEP) and the Fehr–Schmidt inequity aversion utility function onto classical DeGroot consensus dynamics. We propose a phenomenological toy model—the Variational Epistemic Inequity-Aversion (VEIA) framework—wherein agents update internal states by minimizing a multi-criteria heuristic that balances parameterized generative model errors, network alignment pressures, and an epistemic analog of status equity.

Rather than modeling a universally validated biological mechanism, this work functions strictly as a conceptual preprint and a hypothesis-generating framework. We map relative informational uncertainty as a scalar psychological loss parameter and adapt traditional material equity utility into an epistemic status asset context.

The paper outlines the severe mathematical bounds required for local linear-quadratic solvability, includes a reproducible Python simulation routine for a 5-node test network matrix, and proposes a human-subject laboratory experimental methodology via oTree and Maximum Likelihood Estimation (MLE) to evaluate the framework's eventual descriptive utility in computational network sociology.