Research
Sexually Selected Computer Code
“Is DNA to life what code is to computers?”
Overview
This project is a pioneering attempt to blur the line between the digital and biological realms. I present an approach to optimizing computer programs using evolutionary algorithms by recombining their instructions in the same way that DNA is recombined through sexual selection.
The Idea
In biological evolution, sexual reproduction allows successful genetic sequences to be mixed and recombined, producing offspring that may outperform either parent. This project asks: can the same principle be applied to computer programs?
By treating program instructions as genetic material and applying crossover and mutation operators analogous to those in biological sexual reproduction, the algorithm evolves programs toward optimal solutions, without requiring explicit knowledge of the optimal program structure.
Key Concepts
- ▸Evolutionary algorithms inspired by natural selection
- ▸Genetic crossover applied to program instruction sets
- ▸Fitness functions to evaluate program quality
- ▸Emergent optimization without gradient information
The code for this project can be found on Github.