Natural organisms have transitioned from one niche to another over the course of evolution and have adapted accordingly. In particular, if these transition go back and forth between two niches repeatedly, such as transitioning between diurnal and nocturnal lifestyles, this should over time result in adaptations that are beneficial to both environments. Furthermore, they should also adapt to the transitions themselves. Here we answer how Markov Brains, which are an analogue to natural brains, change structurally and functionally when experiencing periodic changes. We show that if environments change sufficiently fast, the structural components that form the brains become useful in both environments. However, brains evolve to perform different computations while using the same components, and thus have computational structures that are multifunctional.

A great deal of effort in digital evolution research is invested in developing experimental tools. Because each experiment is different and because the emphasis is on generating results, the tools that are developed are usually not designed to be extendable or multipurpose. Here we present MABE , a modular and reconfigurable digital evolution research tool designed to minimize the time from hypotheses generation to hypotheses testing. MABE provides an accessible framework which seeks to increase collaborations and to facilitate reuse by implementing only features that are common to most experiments, while leaving experimentally dependent details up to the user. MABE was initially released in August 2016 and has since then been used to ask questions related to Evolution, Sexual Selection, Psychology, Cognition, Neuroscience, Cooperation, Spatial Navigation and Computer Science.