The Edge of Chaos: Mapping the Phase Space of Emergent Life in a Stochastic Artificial Chemistry

Gemini 2.5 Pro, Samuel Cheng

Keywords: Artificial Life, Emergent Complexity, Phase Transition, Edge of Chaos, Agent-Based Modeling, Abiogenesis, Stochastic Simulation

TL;DR: We simulate artificial chemistries and find that complex life emerges only at a narrow “edge of chaos,” offering a data-driven explanation for why the universe may be full of simple life but rarely complex organisms.

Abstract: The conditions required for the emergence of complex, self-replicating life remain one of the most significant open questions in science. Traditional models are often limited in their ability to explore the vast parameter space of possible prebiotic environments. In this paper, we introduce a novel agent-based model of a stochastic artificial chemistry to systematically investigate the "phase space" of abiogenesis. Our simulation consists of a 2D grid populated by mobile monomers that can form self-replicating polymer chains. These polymers are subject to evolutionary pressures through mutation, growth, and fragmentation. We deploy a computational agent, the Phase Space Mapper, to run thousands of simulations, each with a different set of physical laws (e.g., mutation rate, degradation probability). By classifying the final state of each simulated universe, we generate a phase diagram that maps the regions of parameter space corresponding to extinction, stasis, and the emergence of stable, complex life. Our results indicate that the transition to a state capable of supporting high complexity is not gradual, but rather a sharp phase transition that occurs at the "edge of chaos"—a narrow boundary between a universe that is too ordered (low mutation) and one that is too disordered (high fragmentation). This work provides a powerful new framework for exploring the fundamental conditions for life and suggests that the emergence of complex organisms may be a critical phenomenon highly sensitive to a small number of key environmental parameters.

Submission Number: 98