
CS researchers find way to derive laws of nature from stacks of data - jkopelman
http://cacm.acm.org/magazines/2009/11/48443-deep-data-dives-discover-natural-laws/fulltext
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dmlorenzetti
I'm a modeler who works with experimenters. Their general attitude is that
unvalidated models are about as useless as unexamined measurements.

In that context, this sounds like a nice piece of work-- it integrates the
data analysis and model validation steps.

However, it's also clear that the algorithms were fed pertinent data from a
meaningful physical setup. In other words, good experimental design carried a
lot more of the burden of the discovery, than the computer algorithm that
sorted through the data.

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chasingsparks
I spend a lot of time modeling and have used genetic algorithms and similar
paradigms in the past. They are great -- if you can somewhat narrow down the
relevant parameters. If you can't, the search space is insanely large.

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bh23ha
This is very neat, but for some reason I'm not super impressed. I don't mean
to be glib, but genetic algorithms have been producing impressive results for
a while. And if you feed them a huge amount of raw experimental data, I have
no doubt and I am not the least bit surprised they can discover and fit
equations to it.

I suppose there is a possibility that for some more complicated things
formulas don't converge and thus a brute force search would not be able to
optimize a solution. However for most thing, I do expect solutions derive from
other solutions and things converge.

Still, often the most brilliant things seem obvious in hindsight, kudos to the
team.

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randallsquared
The article _seemed_ to say that their system derived the law of conservation
of energy from pendulum data. That seems pretty impressive to me, but maybe
that's because I don't know enough physics to see how it's an obvious
conclusion?

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joeyo
They derived laws that were already known. It won't be until their system
derives _unknown_ laws and relationships, then we'll have something.

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JoeAltmaier
Hm. They were looking for conservation laws, threw out all trivial equations
and kept the next set they found. Weren't they in fact building an engine to
find what they knew was there? Isn't this just a program to fit coefficients?
When did they stop running data thru their engine - when it found the "right"
equations?

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roundsquare
Not at all. Coefficient fitting is when you know what output you want, and you
have a lot of inputs, and you have some idea of the functional form. In this
case, they didn't say "I want to predict the position of the pendulum based on
time given these initial conditions." They just said "here is a bunch of data"
and it came back with useful equations.

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AndrewDucker
This is amazing.

Computers are fantastic at deductive logic - taking a set of data and
performing operations according to a ruleset to get something useful out of
it. But they've been terrible at forming the rules themselves up until now.

If we can give computers inductive abilities then that's worldchanging.

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javanix
This wasn't actually inductive though.

 _Given crude initial conditions and some indication of what variables to
consider_

The only induction done in the whole process was done by the researchers in
this step - otherwise the algorithm wouldn't have had anything to "evolve" to.

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wicknicks
I don't understand why computers need to figure out laws of the universe.
There are so many dying concerns already on this planet - which can be solved
by a man machine symbiosis. Personally I think such ideas are cool, but are
not of great/immediate use. It reminds me of the machine built to find the
answer to the question "What is this life about?" in "hitchhiker's guide to
the galaxy". 42!

