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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."
Problem is, the Club of Rome predicted that everyone in the Western world would either be starving to death or choked in their own waste by the far-off year 2000. Looking out my window today, I see that things are far from perfect, but we have a higher population, more food, and in many respects less pollution than we did in 1975. So the CoR's models were dead wrong.
sPh
You're correct about the models not necessarily being reversable - meaning that you can't predict history from the future. However, the correct method of verifying a simulation as correct is to verify the simulation results against known data. In the article, where it talks about the Anasazi, they describe writing the simulation and then letting it run through they years that they have data about the Anasazi (where the villiages are, the water availability, etc) and comparing it to reality. As described, they got quite close to reality. Villiages ending up in the same spot as reality over 50% of the time, etc. etc. etc.. Remember, it is very hard to determine the cause (or stimulus) from the effect without additional data. However, if the cause (stimulus) is known, the effect is usually fairly easy to guess.
If we were to try to build a model of today's history, you would want to build the model, seed it like the world was in the 1700's or earlier and let it run, and see how often it ended up correct. If it wasn't quite accurate, figure out where your model is wrong, fix, and repeat.
In the Asimov stories, what Hari Seldon was doing was to come up with a set of "formulas" (stored in the prime radiant) which accurately simulated history. The more accurate the formulas and the data you have, the more correct you are going to be. Hari and the members of the Foundation were constantly working on tweaks to better account for errors in the simulation. The hard part is dealing with the truly random influences. For instance, in the article when they talked about the Anasazi, they used real weather data instead of simulating it. I suspect if the weather data was simulated, the simulation would not have been as accurate on a year-to-year basis, although if the weather simulation was realistic enough I suspect that the outcome would have been similar.
Thinking back about Psychohistory as put forward by Asimov, I think that the only thing which really stretches for me is the accuracy (within a few months) of the events which he predicted-- taking into account the numerous variables which have such a rare occurance (such as an asteroid hitting a planet wiping everything out, or another major random event), that it would be throw the accuracy of small-scale events off. It seems logical that you can be accurate on a large scale on a simulation (over many thousands of years) or on a small scale (over a hundred years or so), but not both with the same simulation.
The major problems with the models is that they are not very good at handling technological change that in turn makes fundamental changes in the values the models use to make its predictions.
For example, let's say your population growth model includes a value for "food value produced per acre of land". If something comes along that allows more food to be produced per acre, then that'll skew the models to hell.
This actually happened. A new strain of wheat (?) was produced a few years ago that was able to survive in much tougher conditions, and that single-handedly staved off starvation in India.
The same with waste levels. recycling has become much more prevelent, and modern cars are so much better that they're actually starting to _clean_ the air that passes through them.
The models were accurate the day they were published, but the run conditions have changed since.
DG
Want to learn about race cars? Read my Book
The problem with the "running forward from 1900" test is that the model includes, both explicitly and subconsciously, the model maker's view and understanding of the world that already exists. Including the events that occured between 1900 and 2000, say. So of course you would expect it to show reasonably accurate results for that time period - otherwise it would have been discarded during the development phase. However, that is no guarantee that the model is accurate outside the limits of that perception of the world.
I ran into exactly this problem myself. I developed several system dynamics models that seemed to give a good simulation of the population and wealth of the City of Chicago from 1950 to 1980. But when I ran them starting with the base data for similar cities, I got meaningless results. What seemed on first examination to be a general model of city population was actually just a condensed way of displaying the known state of one particular city.
So stronger tests than just "run forward to known state" are needed. Some argue that human events include irreversible processes, so perhaps the "run backwards" test is not valid. But more is needed than a demonstration between two known states.
sPh
i've done this in other research, it checks out, it's pretty neat to calculate the length of posts/conversations etc, rank them and graph them, and see a zipf distribution pop out. anybody else out there doing this?
The Journal of Artificial Societies and Social Simulation (JASSS). It is on-line. It is free. It is great.
Belief is the currency of delusion.
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A fatal flaw of this simulation (as a model of real society, that is) is that it includes the "Cincinatus" characters - the incorruptible agents - but does not include the "Dillingers" - agents who are not deterred by punishment, of themselves or of others.
I have found over the years that people who are not influenced by "common sense" (or even an informed sense of self-preservation) are much more common than incorruptible people. Luckily (perhaps) these people more commonly are obsessed with greed than killing, or we'd have a lot more mayhem and a few less rich people.
Thus, the simultation should include agents that are not influenced by the arrest rate, and the model will probably become cyclic instead of trending to a fixed equilibrium.
Your statement that "the simulation is accurate" is unfounded, as any serious study of real behaviour in a police state will show. The Chinese shoot homosexuals and drug addicts; yet they still occur just as frequently as in other nations with less draconian laws. The US is "soft on crime" according to the Immoral Minority, yet our crime rates continue to drop.
But of course, anyone who thinks humans are simple agents with simple motivations is very unobservant.
--Charlie