Evolving Markov Brains in virtual environments is one thing, but what happens when you expose Markov Brains to the real world? Here I show two examples where Thassyo Pinto and I tried exactly that. In the first example we evolved Markov Brains to follow a line. We used a fully virtual and fairly abstract environment and selected for controllers to control a bot so that it first finds a line and secondly follows it. However, we either used a simple circle for the bot to follow in order to represent a static environment or a curvy line that changed it’s curvature from generation to generation. The brains were afterwards uploaded to the bot and tested in a real environment. We find that as expected bots evolved in a noisy environment are much more robust to variation in the environment. However, this robustness comes with a price, the more robust bot if slower. Check the video:
