Evolving cheating DNA networks: a Case Study with the Rock–Paper–Scissors Game

Abstract

In models of games, the indirect interactions between players, such as body language or knowledge about the other’s playstyle, are often omitted. They are, however, a rich source of information in real life, and increase the complexity of possible strategies. In the game of rock-paper-scissors, the simple monitoring of the opponent’s move before it was played is a sufficient condition to trigger an arms race of detection and misinformation among evolved individuals. The most interesting aspect of those results is that they were obtained by evolving purely chemical reaction networks thanks to an adapted version of the famous NEAT algorithm. More specifically, those individuals were represented as biochemical systems built on the DNA toolbox, a paradigm that allows both easy in-vitro implementation and predictive in-silico simulation. This guarantees that the specific motives that emerged in this competition would behave identically in a test tube, and thus can be used in a more generic context than the current game.