Engineering Adaptive Gene Circuits in Bacteria Mastering Game Playing by Reinforcement Learning

Abstract

Learning to solve problems is central to artificial and living intelligent systems. Although physical and chemical systems mimicking neural connectivity have been shown to solve complex problems, no living system with a synthetic genetic construction has ever been reported to learn complex algorithms such as playing board games — a classic benchmark for artificial intelligence. Engineering a synthetic genetic system in living cells able to learn and play even the simplest board games, such as tic-tac-toe, has remained elusive because it requires not only a set of gene circuits implementing the needed decision algorithms but also an adaptive memory system that can predictably adjust their strength through learning.