[alife] New paper on why modules evolve, and how to evolve modular artificial neural networks

[Jeff Clune]

Hello all,

I'm extremely pleased to announce a new paper on a subject that many--including myself--think is critical to making significant progress in our field: the evolution of modularity. 

Jean-Baptiste Mouret, Hod Lipson and I have a new paper that 

1) sheds light on why modularity may evolve in biological networks (e.g. neural, genetic, metabolic, protein-protein, etc.)

2) provides a simple technique for evolving neural networks that are modular and have increased evolvability, in that they adapt faster to new environments. The modules that formed solved subproblems in the domain. 

Cite: Clune J, Mouret J-B, Lipson H (2013) The evolutionary origins of modularity. Proceedings of the Royal Society B. 280: 20122863. http://dx.doi.org/10.1098/rspb.2012.2863 (pdf)

Abstract: A central biological question is how natural organisms are so evolvable (capable of quickly adapting to new environments). A key driver of evolvability is the widespread modularity of biological networks—their organization as functional, sparsely connected subunits—but there is no consensus regarding why modularity itself evolved. Although most hypotheses assume indirect selection for evolvability, here we demonstrate that the ubiquitous, direct selection pressure to reduce the cost of connections between network nodes causes the emergence of modular networks. Computational evolution experiments with selection pressures to maximize network performance and minimize connection costs yield networks that are significantly more modular and more evolvable than control experiments that only select for performance. These results will catalyse research in numerous disciplines, such as neuroscience and genetics, and enhance our ability to harness evolution for engineering purposes.

Video: http://www.youtube.com/watch?feature=player_embedded&v=SG4_aW8LMng

There has been some nice coverage of this work in the popular press, in case you are interested:

National Geographic: http://phenomena.nationalgeographic.com/2013/01/30/the-parts-of-life/
MIT's Technology Review: http://www.technologyreview.com/view/428504/computer-scientists-reproduce-the-evolution-of-evolvability/ 
Fast Company: http://www.fastcompany.com/3005313/evolved-brains-robots-creep-closer-animal-learning
Cornell Chronicle: http://www.news.cornell.edu/stories/Jan13/modNetwork.html
ScienceDaily: http://www.sciencedaily.com/releases/2013/01/130130082300.htm

Please let me know what you think and if you have any questions. I hope this work will help our field move forward!



Best regards,
Jeff Clune

Assistant Professor
Computer Science
University of Wyoming
jclune at uwyo.edu
jeffclune.com