---
layout: single
title:  "Social NN-Soup"
categories: research audio deep-learning anomalie-detection 
excerpt: "Social interaction based on surprise minimization"
header:
  teaser: assets/figures/18_surprised_soup_teaser.jpg
---

![Social Soup Schematics](\assets\figures\18_surprised_soup_schematic.jpg){:style="display:block; width:40%" .align-right}
This research explores artificial chemistry systems with neural network particles that exhibit self-replication. Introducing interactions that enable these particles to recognize and predict each other's behavior, the study observes emergent behaviors akin to stability patterns previously seen in explicit self-replication training. A unique catalyst particle introduces evolutionary pressure, demonstrating how 'social' interactions among particles can lead to complex, emergent outcomes.
{% cite zorn23surprise %}

![Soup Trajectories](\assets\figures\18_surprised_soup_trajec.jpg){:style="display:block; width:90%" .align-center}