# The evolutionary origins of hierarchy

arXiv: https://arxiv.org/abs/1505.06353 · HTML: https://mlsanity.com/paper/1505.06353/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 May 2015.

## Built on by (most cited first, 9 of 9)

- [Seeing is Believing: Brain-Inspired Modular Training for Mechanistic Interpretability](https://mlsanity.com/paper/2305.08746/) (2023)
- [Hierarchical clustering with dot products recovers hidden tree structure](https://mlsanity.com/paper/2305.15022/) (2023)
- [Foundations of a Developmental Design Paradigm for Integrated Continual Learning, Deliberative Behavior, and Comprehensibility](https://mlsanity.com/paper/2502.13935/) (2025)
- [On the Parallels Between Evolutionary Theory and the State of AI](https://mlsanity.com/paper/2505.23774/) (2025)
- [Neural Sculpting: Uncovering hierarchically modular task structure in neural networks through pruning and network analysis](https://mlsanity.com/paper/2305.18402/) (2023)
- [Evolutionary Developmental Biology Can Serve as the Conceptual Foundation for a New Design Paradigm in Artificial Intelligence](https://mlsanity.com/paper/2506.12891/) (2025)
- [Pruning Increases Orderedness in Recurrent Computation](https://mlsanity.com/paper/2507.14747/) (2025)
- [Lessons from Neuroscience for AI: How integrating Actions, Compositional Structure and Episodic Memory could enable Safe, Interpretable and Human-Like AI](https://mlsanity.com/paper/2512.22568/) (2025)
- [Minimalist Genetic Programming](https://mlsanity.com/paper/2606.10237/) (2026)

## Abstract (arXiv)

Hierarchical organization -- the recursive composition of sub-modules -- is ubiquitous in biological networks, including neural, metabolic, ecological, and genetic regulatory networks, and in human-made systems, such as large organizations and the Internet. To date, most research on hierarchy in networks has been limited to quantifying this property. However, an open, important question in evolutionary biology is why hierarchical organization evolves in the first place. It has recently been shown that modularity evolves because of the presence of a cost for network connections. Here we investigate whether such connection costs also tend to cause a hierarchical organization of such modules. In computational simulations, we find that networks without a connection cost do not evolve to be hierarchical, even when the task has a hierarchical structure. However, with a connection cost, networks evolve to be both modular and hierarchical, and these networks exhibit higher overall performance and evolvability (i.e. faster adaptation to new environments). Additional analyses confirm that hierarchy independently improves adaptability after controlling for modularity. Overall, our results suggest that the same force--the cost of connections--promotes the evolution of both hierarchy and modularity, and that these properties are important drivers of network performance and adaptability. In addition to shedding light on the emergence of hierarchy across the many domains in which it appears, these findings will also accelerate future research into evolving more complex, intelligent computational brains in the fields of artificial intelligence and robotics.