Evolving Symbiosis, from Barricelli's Legacy to Collective Intelligence: a simulated and conceptual approach

2026-03-09

AI Summary

This study investigates how symbiotic mechanisms drive the emergence of life’s origins, open-ended evolution, and collective intelligence. Building upon Barricelli’s 1953 numerical model of symbiotic organisms, we extend the original one-dimensional cellular automaton into a two-dimensional spatial framework and introduce a DNA-norms mechanism to regulate symbiotic interactions. By successfully reproducing classic experiments and achieving stable evolution of two-dimensional symbionts, our work not only confirms the pivotal role of symbiosis in artificial life systems but also establishes a novel pathway for implementing open-ended evolution and collective intelligence on substrates such as neural networks and neural cellular automata.

Technology Category

• Intelligent Robots: Embodied AI
• Multiagent Systems: Agent-Based Simulation and Emergent Behavior
• Machine Learning: Evolutionary Learning

Application Category

• Web Mining and Content Analysis: Models for Web evolution
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs

Abstract

This report documents the work of our group (named SymBa) at the ALICE 2026 workshop in Copenhagen. Inspired by the pioneering work by Nils Aall Barricelli on symbiogenesis of numerical organisms (i.e., 1D cellular automata) in 1953 (70+ years ago!!), we discussed the role of symbiogenesis as mechanism contributing to the origins of life, open-endedness, and collective intelligence. We report replications of Barricelli's original work in 1D worlds, an extension to 2D symbioorganisms, and preliminary experimentation with DNA-norms. We discuss the implications of symbiogenesis for artifical life and artificial intelligence, and outline several opportunities for future works, both at the conceptual level as well as using different substrates (neural networks, neural cellular automata, etc.)

Problem

• symbiogenesis
• origin of life
• open-endedness
• collective intelligence
• artificial life

Innovation

• symbiogenesis
• cellular automata
• collective intelligence
• open-ended evolution
• DNA-norms