---
layout: single
title:  "Organism Networks"
categories: research audio deep-learning anomalie-detection 
excerpt: "Constructing ON from Collaborative Self-Replicators"
header:
  teaser: assets/figures/16_on_teaser.jpg
---

![Organism Network Architecture](\assets\figures\16_on_architecture.jpg){:style="display:block; width:65%" .align-center}

This work delves into the concept of self-replicating neural networks, focusing on how backpropagation facilitates the emergence of complex, self-replicating behaviors. 
![Dropout](\assets\figures\16_on_dropout.jpg){:style="display:block; width:45%" .align-right}
By evaluating different network types, the study highlights the natural emergence of robust self-replicators and explores their behavior in artificial chemistry environments.
A significant extension over a previous version, this research offers a deep analysis of fixpoint weight configurations and their attractor basins, advancing the understanding of neural network self-replication.

For more detailed insights, refer to {% cite illium2022constructing %}.