Emergence of Active Inference from a Chemical Oscillator: A Constructive Approach to Pre-genetic Homeostasis

TL;DR

This paper presents a minimal chemical model demonstrating how primitive life could achieve homeostasis and adapt to environmental changes through emergent active inference mechanisms, predating genetic systems.

Contribution

It introduces a chemically plausible model where active inference emerges from a simple reaction network, illustrating a potential origin of adaptive behavior in early life.

Findings

Model autonomously converges to optimal conditions for self-replication.

System maintains homeostasis despite environmental fluctuations.

Active inference can emerge from basic chemical oscillators.

Abstract

How could primordial life, before the evolution of genetic systems, adapt to fluctuating environments and achieve homeostasis? This study proposes a minimal, chemically plausible model where homeostasis emerges from a simple chemical reaction network. It utilizes an internal Lotka-Volterra chemical oscillator as a "search engine" to periodically vary a protocell's pigmentation. The system then optimizes its internal state by evaluating the temporal correlation between these internal fluctuations and a single global metric,the cell's self-replication rate, through a mechanism termed "antagonistic memory molecules." Numerical simulations demonstrate that the model can autonomously converge to and maintain the optimal temperature for its self-replication, even amidst significant environmental fluctuations. These findings provide a constructive proof-of-concept for how a core process of active inference can emerge from a simple physicochemical system, offering a concrete scenario for the acquisition of adaptive capabilities at the origin of life.