Cooption and Catalysis in a Model of Technological Evolution

Most evolutionary algorithms ultimately focus on optimizing solutions to a single target function, coevolution and related methods notwithstanding. Cooptive phenomena between organisms adapted to distinct environmental niches, however, lie at the heart of the evolution of complex functions in nature and technology, where solutions adapted for one problem are repurposed to solve another, related problem. Boolean functions have become a popular toy model for exploring the dynamics of such processes, and provide insight into new approaches to evolutionary computation. We implemented the basics of a model of combinatorially evolving logic circuits developed by Brian Arthur and Wolfgang Polak, and began to explore the sort of cooptive and catalytic phenomena its success depends upon. We observed a significant difference in the dynamics of evolution between when the full suite of fitness functions is present, versus when only a few pieces of the selective pressure are active at a time. Future work will examine these dynamics in more detail.