# Ants, robots, humans: a self-organizing, complex systems modeling approach

arXiv: https://arxiv.org/abs/2009.10823 · HTML: https://mlsanity.com/paper/2009.10823/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Sep 2020.

## Built on by (most cited first, 2 of 2)

- [The Free-Market Algorithm: Self-Organizing Optimization for Open-Ended Complex Systems](https://mlsanity.com/paper/2603.24559/) (2026)
- [Cost-Penalized Fitness in FMA-Orchestrated Mixture of Experts: Experimental Evidence for Molecular Memory in Domain Adaptation](https://mlsanity.com/paper/2604.00812/) (2026)

## Abstract (arXiv)

Most of the grand challenges of humanity today involve complex agent-based systems, such as epidemiology, economics or ecology. However, remains as a pending task the challenge of identifying the general principles underlying their self-organizing capabilities. This article presents a novel modeling approach, capable to self-deploy both the system structure and the activities for goal-driven agents that can take appropriate actions to achieve their goals. Humans, robots, and animals are all endowed with this type of behavior. Self-organization is shown to emerge from the decisions of a common rational activity algorithm, based on the information of a system-specific goals dependency network. The unique self-deployment feature of this approach, that can also be applied to non-goal-driven agents, can boost considerably the range and depth of application of agent-based modeling.