Steve Verdon has a thought-provoking post with good links on the potential value of a synthesis of Austrian economics and evolutionary game theory that focuses on learning. One of the problems even for the more sophisticated models of learning in games is that the economist still pretty much has to specify the environment, and if you have to specify the rules by which the system evolves, you have to do it deftly to avoid just having the “evolution” be replication. So I’ll be very interested to follow his links and see if we’re converging on a valuable synthesis.
One sticker for me is going to be that in Austrian economic theory, one of the important features is that through the process of competition you learn both what your preferences are and what the opportunity set is. Game theoretic models usually fix those dimensions to make the models more tractable. And how do you formally handle the fact that not everything can have a probability distribution fit to it — in Frank Knight’s terms, we face not just risk but also uncertainty. Formal models don’t do a good job of capturing the joint dynamics of the discovery process and the omnipresence of uncertainty, not just risk, on some dimensions.
So thanks to Steve for the post and the links. I’ll check them out.