Former SFI Science Board Member Frances Arnold was awarded the 2018 Nobel Prize in Chemistry for pioneering directed evolution to design new and improved enzymes. Arnold transformed bioengineering by harnessing the power of evolution, and now the field of evolutionary computation is applying her process within a computational framework to solve computational problems.
In a perspective piece published in Nature Machine Intelligence in January 2021, SFI External Professor Stephanie Forrest (Arizona State University) and co-author Risto Miikkulainen (University of Texas at Austin), describe evolutionary computation (EC), an approach to engineering digital systems that seeks to replicate aspects of Darwinian evolution. They describe how evolutionary computation compares to biological evolution — and how it diverges in three key ways.
Forrest and Miikkulainen found that “evolutionary computation is based on small populations and strong selection; it typically uses direct genotype-to-phenotype mappings; and it does not achieve major organizational transitions.” They say these shortcomings suggest a roadmap for future evolutionary computation that may approach the complexity and flexibility of biology.
Read the paper, "A biological perspective on evolutionary computation," in Nature Machine Intelligence (January 18, 2021)
Read Arizona State University's Q&A with Forrest (January 18, 2021)