Chapter 2 is a nice piece on the El Farol Problem which is a paradox which “represented a decision problem where expectations (forecasts) that many would attend [the El Farol bar] would lead to few attending, and expectations that few would attend would lead to many attending: expectations would lead to outcomes that would negate these expectations.”
Zhang and Challet generalized this problem into the Minority Game in game theoretic form.
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There are two reasons for perfect or deductive rationality to break down under complication. The obvious one is that beyond a certain level of of complexity human logical capacity ceases to cope–human rationality is bounded. The other is that in interactive situations of complication, agents cannot rely upon the other agents they are dealing with to behave under perfect rationality, and so they are forced to guess their behavior. This lands them in a world of subjective beliefs and subjective beliefs about subjective beliefs. Objective, well-defined, shared assumptions then cease to apply. In turn, rational, deductive reasoning (deriving a conclusion by perfect logical processes from well-defined premises) itself cannot apply. The problem becomes ill-defined.
This passage, though in an economics text, seems to be a perfect statement about part of the problem of governing in the United States at the moment. I have a thesis that Donald Trump is a system 1 thinker and is generally incapable of system 2 level thought, thus he has no ability to discern the overall complexity of the situations in which he finds himself (or in which the United States finds itself). As a result, he’s unable to effectively lead. From a complexity and game theoretic standpoint, he feels he’s able to perfectly play and win any game. His problem is that he feels like he’s playing tic-tac-toe, while many see at least a game as complex as checkers. In reality, he’s playing a game far more complex than either chess or go.
The overall problem laid out in this chapter is an interesting one vis-a-vis the issues many restaurant startups face, particularly in large cities. How can they best maximize their attendance not only presently, but in the long term while staying afloat in very crowded market places.
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The level at which humans can apply perfect rationality is surprisingly modest. Yet it has not been clear how to deal with imperfect or bounded rationality.
Chapter 3 takes a similar problem as Chapter 2 and ups the complexity of the problem somewhat substantially. While I understand that at the time these problems may have seemed cutting edge and incomprehensible to most, I find myself wondering how they didn’t see it all from the beginning.
http://happy-foxie.com/trump-just-revealed/
http://happy-foxie.com/pastor-to-trump-supporters-stop/
The challenge is that many of our models for economics and finance assume an informed person making rational decisions. Not all people have access to the same information or choose to do the research or have the same capacity to understand the information. (I just had an uber driver who used to be a math professor specializing in probability. He went on to put together lottery programs for several states. I guarantee my approach to finance and stocks is rudimentary at best compared to his – and would be no matter how much research I did). And that’s without getting into the rational part your post so eloquently discusses.
The first part of this book gets into some of the interesting specifics and builds using several rudimentary examples. Thus far it’s all overview narrative without any dense mathematics, so it’s not a bad primer for a broader public. I will note that it’s comprised of journal articles by the author, so most may be freely available on the web without shelling out the money for the book itself.