The blockchain application called cryptokitties provides some interesting ideas about genetic and evolution algorithms and the market. In classical evolution and genetic algorithms there is usually a target or fitness function to evaluate a certain population or individual and the goal is to minimize the difference between target value and the actual performance of the population. However the whole concept might be put into a market context. The mutated or combined entities of the population are exchanged or traded between different actors. As the time goes on, high value individuals are traded frequently or for a high price as less important individuals will have low liquidity and low price. Certainly, in this way the target value that is evaluated in each round depends on the subjective evaluation of the individuals taking part in the trade. As these subjective preferences might evolve over the time, it is pretty questionable in which direction does the algorithm converge.
