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Is a Theory Generation Program possible?

  1. Dec 26, 2007 #1
    Since many problems in physics are proving difficult, would it be possible to create a theory generator? It would be set to focus on one problem, like quantum gravity. It would be fed experimental results and goals and then be set free to evolve theories that produced those results. Has this been tried or is it just too difficult a programming task at the moment?

    At the very least, how about an idea generator that might spark insight into the problem. It might contain general concepts and mathematical relationships that are combined randomly, like a band name generator.

    Perhaps the idea generator can help seed the theory generator.
    Last edited: Dec 26, 2007
  2. jcsd
  3. Dec 26, 2007 #2


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    Shouldn't you set out to do a "proof-of-principle" first rather than going ahead and trying to solve an unsolved problem?

    Try setting up a simple "theory generator" on, oh, something simpler like the Special Theory of Relativity that has been verified already. If you can't find that it can be done, what hope do you have for solving more difficult and unverified ones? This is how science, and especially physics, is done. A better "technique" should show that it can work in areas that we know already.

    And oh, my opinion here is that there is no such thing as a 'theory generator'.

  4. Dec 26, 2007 #3
    - Definitely.

    - Well, the brain is a theory generator so I would think an AI would be capable of it as well. If we could create AI smarter than we are, that should do the trick - but that will take too long. I don't think theory generation requires intelligence though, so we might be able to build a generator before we are able to create AI.
  5. Dec 26, 2007 #4

    jim mcnamara

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  6. Dec 26, 2007 #5
    Yeah...something like that. Why not expand that into physics?
  7. Dec 26, 2007 #6

    jim mcnamara

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    Non-psychotic humans are capable of inductive and deductive reasoning - whether or not they know what those terms mean.

    Generating theories means taking relevant observations (knowing whether they are relevant or questionable is pretty much beyond AI algorithms now), and then constructing a general statement which explains all of those observations. Then you repeatedly test with new observations. ZZ and the OP covered that pretty well.

    So, we have issues:
    1. which observations to keep, which to pitch, and why were they pitched.
    It is possible to construct a nifty, interesting, and wrong hypothesis by just tossing and keeping examples until you get a combination where everything fits a bogus hypothesis
    -- listen to any politician or Rush Limabaugh for endless examples.

    2. how to establish any hypothesis generated really accomplishes any meaningful explaining - another AI problem as well.

    3. how to establish the system works correctly on known problems and solutions.
    This was mentioned.
  8. Dec 26, 2007 #7
    I thought the problem of QG was too many theories and not enough experimental results.
    Last edited: Dec 26, 2007
  9. Dec 26, 2007 #8
    --Yes, and actually that would be a good thing, since it might spark some new insight. The computer would probably come up with some wacky stuff. You'd have to explain why it was wrong and might learn something in the process. But it also might stumble into the truth.
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