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Simulating Societies
blamanj writes "Most of us were exposed fairly early to Conway's game of Life.
A few simple rules produce a fascinating variety of behavior. Now, it
appears that similar simulations can predict the behavior of populations and human societies."
This article is really describing modeling using multiagent systems. Though very simple multiagent systems may resemble cellular automata (such as Conway's Life), they are not the same thing. Though they have been described in very convenient graphical representations using grids in the article, agents can model more complex behavior and need not be determinisitic (i.e. they may have a random element).
Another way to look at it is that cellular automata like Life use a single deterministic rule to govern the whole system. Agent-based systems, on the other hand, model goal-oriented behavior of the individual objects.
Again, Conway's game can be viewed as a very special case of an simple agent system, but the spirit of what is being done with agent systems is typically more involved. Comparing these systems to Conway's game of Life may create an incorrect impression for those not familiar with agent programming.
Hmmm... So the simulation is accurate, but I would hypothesize that it does not show that a free society will trend towards "honesty."
Nonperiodic Central Trajectory
Ref. the first post: Hari Seldon's (OK, Isaac Asimov's) theory of Psychohistory has as it's base theorem that the behavior of individual humans is unpredictable, but the behavior of large groups of humans is predictable to within statistical limits. And if you think he's wrong, ask about marketing profiles and even Amazon's recommendations system.
"As God is my witness, I thought turkeys could fly." A. Carlson
The problems lie elsewhere. Two that come to mind quickly are (1) lack of agreed upon factual data to use as the basis of the hypotheses. Do people with green skin have more or fewer babies out of wedlock than people with orange skin, and has this number increased or decreased over the last 10 years? Even in the US, with the Census data and tremendous amounts of market research, there are no agreed-upon answers to fundamental questions of data. Plenty of Newtons but no Kepler.
(2) None of these models are reversible. Put in a starting point of today's conditions, set the time increment to -1, and run the simulation backwards for 100 years. What comes out will be nothing like the world as it actually was in 1900. If we can't accuratly predict what happened in the past, how can we have any belief that the models tell us anything meaningful about the future?
sPh
But that's exactly what the corruption/honesty simulation is trying to argue against. It is saying that traditional social science modelling is fundamentally flawed because it assumes everyone in a particular group behaves the same and has unlimited knowledge.
A social model that viewed individuals as multiple copies of the same fully informed person could thus never "see" the social transformation that Hammond found, for the simple reason that without diversity and limited knowledge, the transformation never happens. Given that human beings are invariably diverse and that the knowledge at their disposal is invariably limited, it would seem to follow that even societies in which unsophisticated people obey rudimentary rules will produce surprises and discontinuities--events that cannot be foreseen either through intuition or through the more conventional sorts of social science.
From what the article describes, the people doing these experiments have got their research backwatds. Specficially finding that a particular set of assumptions to a simulation generates a result 'like' human society is meaningless unless you also show that the assumptions are legitimate. The racism example was particularly egregious; nowhere is it explained why ignoring the effect of income distribution, access to jobs, the actions of the government, etc on where people lived was valid. It gives the strong impression that showing that racial division arises from inscrutable preferences is attractive for political reasons more than anything.
The article reminded me of the old story of the experimentall physicist who runs excitedly up to his theorist colleague, exclaiming "Look! I can show that A > B!" The theorist says, "That's easy to explain. [Explanation deleted...]" The experimentalist says, "Did I say A > B? I meant B > A.", to which the theorist replies, "Oh, that's even easier to explain."
The models described seem far too simple to describe something as complicated as society. As a physicist who has dabbled in biology, I know the perils of applying simple models to biological systems. How sensitive are these models to the addition of another type of interaction between people, or another outside influence? For every simple model that shows A>B, I can come up with one that shows B>A, unless the simple model is very well rooted in fhe fundamental physics (or sociology) of the problem. I don't believe that the fundamentals of sociology are well enough established to make these models believable.
For example, consider the Schelling model of segregation discussed in the article. From a physicist's point of view, this is a statisictal simulation of a system of two types of particles on a lattice, with an attractive interaction between particles of the same type. There's no temperature, so the system will phase separate, since that's the lowest energy state. No surprise there. A five minute chat with a physicist could have saved Schelling a lot of computer time. The more interesting question is what happens when you add some randomness in the form of temperature. Then the system will phase separate below a certain temperature, and form a single mixed phase above that temperature. What is the sociological analog of temperature? (Ok, I know that one... If a particle of one type is hot for a particle of another type, then you get particles of mixed type....)
The simulations are cute and I'm sure they're fun to play with, but I wouldn't put much stock in them.
-- Steve
Lost: one sig, witty, 120 chars, sentimental value. Reward offered.
The program that ended up as the most successful was also the simplest. University of Toronto Game Theorist Anatol Rappaport had submitted a program he called tit for tat. Tit for tat initially cooperated with all the other players. In subsequent turns if the other player it was interacting with had defected last turn, it defected this turn. If the other player had cooperated last turn it cooperated this turn.
Yes, the interactions between people are very complicated, and this game is very simple. Still food for thought though.
A model pictures reality by simplifying it. This research is emulation.... The problem is that everyone KNOWS the outcomes. The IMPORTANT question is whether the underlying assumptions catch the true causal forces.
And there are real problems with this school of thought, not the least of which is its claim that getting complex interactions out of simple assumptions is any harder than getting complex interactions out of a great deal of assumptions. It should be self-evident that complexity in this type of research stems largely from the number of actors, not the determinants of their behavior.
Deeper problems include assumptions of rationality and intentionality on the part of actors. There is also a tendency towards selection bias and selectivity THAT IS NEVER ADDRESSED. IE, this author may think he explains ethnic genocide in Rwanda, but never points out that his logic fails miserable in places like Switzerland, Brazil, Mexico, Russia and much of the Middle-East, where his model would predict much MORE conflict than we see.
Do you also support Disney's position that I should have to pay them a royalty every time I watch a DVD that I purchased? I won't buy DVDs or CDs or anything else under that plan, and I won't buy books under your plan. Period. If you want to kill your market, go right ahead -- there's pleanty of other entertainment sources that take a more reasonable view.
If all this should have a reason, we would be the last to know.