The evolutionary origins of hierarchy

Mengistu H
Huizinga J
Mouret JB
Clune J

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.

Full Citation: Mengistu H, Huizinga J, Mouret JB, Clune J (2016) The evolutionary origins of hierarchy. PLoS Computational Biology. (pdf)

Figure 1: The main hypothesis. Evolution with selection for performance only results in non-hierarchical and non-modular networks, which take longer to adapt to new environments. Evolving networks with a connection cost, however, creates hierarchical and functionally modular networks that can solve the overall problem by recursively solving its sub-problems. These networks also adapt to new environments faster.

Talk at the Santa Fe Institute: Two Projects in BioInspired AI. Evolving regular, modular, hierarchical neural networks, and robot damage recovery.

Talk at the Santa Fe Institute: Two Projects in BioInspired AI. Evolving regular, modular, hierarchical neural networks, and robot damage recovery.

Pub. Info: 
PLoS Computational Biology
article{10.1371/journal.pcbi.1004829, author = {Mengistu, Henok AND Huizinga, Joost AND Mouret, Jean-Baptiste AND Clune, Jeff}, journal = {PLoS Comput Biol}, publisher = {Public Library of Science}, title = {The Evolutionary Origins of Hierarchy}, year = {2016}, month = {06}, volume = {12}, url = {}, pages = {1-23}, abstract = {Hierarchy is a ubiquitous organizing principle in biology, and a key reason evolution produces complex, evolvable organisms, yet its origins are poorly understood. Here we demonstrate for the first time that hierarchy evolves as a result of the costs of network connections. We confirm a previous finding that connection costs drive the evolution of modularity, and show that they also cause the evolution of hierarchy. We further confirm that hierarchy promotes evolvability in addition to evolvability caused by modularity. Because many biological and human-made phenomena can be represented as networks, and because hierarchy is a critical network property, this finding is immediately relevant to a wide array of fields, from biology, sociology, and medical research to harnessing evolution for engineering.}, number = {6}, doi = {10.1371/journal.pcbi.1004829} }