Emergent Collective Reproduction via Evolving Neuronal Flocks

Nam H. Le, Richard Watson, Mike Levin, Chrys Buckley
9/20/2024
q-bio.PEcs.AIcs.NE

No official code found. Best implementation: namlehai90/Evolving-Neuronal-Flocks (3 stars, MIT, last commit 2025-07-25).

Abstract

This study facilitates the understanding of evolutionary transitions in individuality (ETIs) through a novel artificial life framework, named VitaNova, that intricately merges self-organization and natural selection to simulate the emergence of complex, reproductive groups. By dynamically modelling individual agents within an environment that challenges them with predators and spatial constraints, VitaNova elucidates the mechanisms by which simple agents evolve into cohesive units exhibiting collective reproduction. The findings underscore the synergy between self-organized behaviours and adaptive evolutionary strategies as fundamental drivers of ETIs. This approach not only contributes to a deeper understanding of higher-order biological individuality but also sets a new precedent in the empirical investigation of ETIs, challenging and extending current theoretical frameworks.

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Code Implementations(1)

MIT

A detailed artificial life simulation that explores emergent collective behaviors and evolutionary transitions in individuality through evolving neural networks.

30PythonSep 20, 20241 years agoMIT

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Cite this paper

@article{le2024emergent,
  title  = {Emergent Collective Reproduction via Evolving Neuronal Flocks},
  author = {Nam H. Le and Richard Watson and Mike Levin and Chrys Buckley},
  year   = {2024},
  eprint = {2409.13254},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2409.13254v1}
}

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