---
layout: single
title: "Organism Network Emergence"
categories: research
tags: artificial-life complex-systems neural-networks self-organization emergent-computation
excerpt: "Self-replicating networks collaborate forming higher-level Organism Networks with emergent functionalities."
header:
  teaser: /assets/figures/16_on_teaser.jpg
scholar_link: "https://scholar.google.de/citations?user=NODAd94AAAAJ&hl=en"
---

This research investigates the transition from simple self-replication to higher levels of organization by exploring how populations of basic, self-replicating neural network units can form **"Organism Networks" (ONs)** through **collaboration and emergent differentiation**. Moving beyond the replication of individual networks, the focus shifts to the collective dynamics and functional capabilities that arise when these units interact within a shared environment (akin to an "artificial chemistry").

<center>
  <img src="/assets/figures/16_on_architecture.jpg" alt="Diagram showing individual self-replicating units interacting to form a larger Organism Network structure" style="display:block; width:65%">
  <figcaption>Conceptual architecture of an Organism Network emerging from interacting self-replicators.</figcaption>
</center><br>

The core hypothesis is that through local interactions and potentially shared environmental feedback, initially homogeneous populations of self-replicators can spontaneously develop specialized roles or structures, leading to a collective entity with capabilities exceeding those of individual units.

![Visualization potentially related to network robustness, differentiation, or communication channels.](\assets\figures\16_on_dropout.jpg)
{:style="display:block; width:45%" .align-right}

Key aspects explored in this work include:

*   **Mechanisms for Collaboration:** Investigating how communication or resource sharing between self-replicating units can be established and influence collective behavior.
*   **Emergent Differentiation:** Analyzing scenarios where units within the population begin to specialize, adopting different internal states (weight configurations) or functions, analogous to cellular differentiation in biological organisms.
*   **Formation of Structure:** Studying how interactions lead to stable spatial or functional structures within the population, forming the basis of the Organism Network.
*   **Functional Advantages:** Assessing whether these emergent ONs exhibit novel collective functionalities or improved problem-solving capabilities compared to non-interacting populations. (The role of dropout, as suggested by the image, might relate to promoting robustness or specialization within this context).

This study bridges the gap between single-unit self-replication and the emergence of complex, multi-unit systems in artificial life research, offering insights into how collaborative dynamics can lead to higher-order computational structures. For more detailed insights, refer to {% cite illium2022constructing %}.

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