---
layout: single
title:  "Self-Replication Goals"
categories: research audio deep-learning anomalie-detection 
excerpt: "Combining replication and auxiliary task for neural networks."
header:
  teaser: assets/figures/13_sr_teaser.jpg
---

![Self-Replicator Analysis](\assets\figures\13_sr_analysis.jpg){:style="display:block; width:80%" .align-center}

This research delves into the innovative concept of self-replicating neural networks capable of performing secondary tasks alongside their primary replication function. By employing separate input/output vectors for dual-task training, the study demonstrates that additional tasks can complement and even stabilize self-replication. The dynamics within an artificial chemistry environment are explored, examining how varying action parameters affect the collective learning capability and how a specially developed 'guiding particle' can influence peers towards achieving goal-oriented behaviors, illustrating a method for steering network populations towards desired outcomes.
{% cite gabor2021goals %}