Herb Simon: computers are pattern-crunchers

[gusl]

One of the central ideas motivating my research is expressed by Herb Simon in the following quote:

Q: So you have moved from field to field as you could bring new tools to bear on your study of decision making?

A: I started off thinking that maybe the social sciences ought to have the kinds of mathematics that the natural sciences had. That works a little bit in economics because they talk about costs, prices and quantities of goods. But it doesn't work a darn for the other social sciences; you lose most of the content when you translate them to numbers.

So when the computer came along -- and more particularly, when I understood that a computer is not a number cruncher, but a general system for dealing with patterns of any type -- I realized that you could formulate theories about human and social phenomena in language and pictures and whatever you wanted on the computer and you didn't have to go through this straitjacket of adding a lot of numbers.

As Dijkstra said, Computer Science is not about computers. It is about processes.

It is a very common error is for people to make an argument like the following:

Stock prices have to do with human behavior. Therefore they are unpredictable. It's not like physics, where computers and mathematical models are useful.

I go all "oy vey" whenever I hear arguments like this... and then, they accuse me of reductionism.

My mom doesn't like it when I interview doctors trying to formalize their knowledge about my problem, so I can truly understand my problems. At the same time, she says (non-sarcastically) I should go into biomedical research.

Comments

[combinator.livejournal.com]

Stock prices have to do with human behavior. Therefore they are unpredictable.

I think this is strongly related to the concept of free will. It's a common religious axiom: even though God is omnipotent, he so generously gave us free will so that he could hold us responsible for screwing up. Since stock prices are a product of free will, they too cannot be controlled by God or simulated by a computer. Of course, if you believe that free will is implemented by a physical system, and you believe physics can be modelled by a computer...

[peamasii.livejournal.com]

Stock prices can definitely be plotted according to mathematical formulas, therefore mathematical models are used in determining all kinds of parameters for stock prices (volatility, trends, relative strength, averages, retracements, support/resistance, targets). It's naive to claim that mass behaviour in the capital markets cannot be quantified mathematically.

[selfishgene.livejournal.com]

The big problem with mathematical models of human behavior, is that humans can reason. If they know there is a model of their behavior, they can attempt to 'game' that model. Suppose the model says that, if is X is true about a company, then the stock price will increase. If I know indicator X will cause investors to buy my stock, I have an incentive to fake X by some method.

[neelk]

The unpredictability of stock prices has nothing to do with free will.

Suppose that there is a function which takes in all public information about the state of the market and then accurately predicts the change in tomorrow's stock price. Whenever the predicted price is higher than today's price, then you can buy stock today, and sell it tomorrow. (Likewise, when the price tomorrow is lower, you can short-sell.) Since this is a profit opportunity, everyone in the market will try to do this, bidding up the price of stock today until there aren't any more profit opportunities. This contradicts our assumption that you can predict future stock prices, so therefore you can't.

This argument makes no assumption at all about the amount of computational power in the prediction function; with infinite computational resources you get a random walk, and if you limit the amount of computation you can do, you'll get various computable approximations to random walks.

[gustavolacerda.livejournal.com]

In other words, you accept the Efficient Markets Hypothesis.


<< Since this is a profit opportunity, everyone in the market will try to do this >>
This only follows if:
* the function is known by everyone in the market
* everyone in the market knows that the function accurately predicts the change in tomorrow's stock price

[neelk]

This is a specific instance of a much larger phenomenon: whenever you have intelligent agents interacting, randomness often shows up as an essential feature. For example, think of the rock-paper-scissors game; the Nash equilibrium in this game is to play randomly.

[gustavolacerda.livejournal.com]

the Nash equilibrium in this game is to play randomly.

This is only the case because your opponents would end up learning any patterns that you played. But this very same fact suggests that it may be better to start using a pattern deceptively, and then do the opposite as soon as your opponents try to use it on you.


I'm glad you qualified it with "often" (when I saw the "whenever", I thought you were being overly general).

Intelligence tends to be more useful in environments that change often. In such environments, if competitive, there are often situations where it's useful to do exactly what people would least expect you to do.