Matt,
I'm not sure I buy that argument for the simple reason that we have massive
cheap processing now and pretty good knowledge of the initial conditions of
life on our planet (if we are going literal here and not EC in the
abstract), but it's definitely a possible answer. Perhaps not enough people
have attempted to run evolutionary computation experiments at these massive
scales either.
Rob
On Mon, Jun 21, 2010 at 12:59 PM, Matt Mahoney <matmaho...@yahoo.com> wrote:
> rob levy wrote:
> > On a related note, what is everyone's opinion on why evolutionary
> algorithms are such a miserable failure as "creative machines", despite
> their successes in narrow optimization problems?
>
> Lack of computing power. How much computation would you need to simulate
> the 3 billion years of evolution that created human intelligence?
>
>
> -- Matt Mahoney, matmaho...@yahoo.com
>
>
> ------------------------------
> *From:* rob levy <r.p.l...@gmail.com>
> *To:* agi <agi@v2.listbox.com>
> *Sent:* Mon, June 21, 2010 11:56:53 AM
>
> *Subject:* Re: [agi] An alternative plan to discover self-organization
> theory
>
> (I'm a little late in this conversation. I tried to send this message the
> other day but I had my list membership configured wrong. -Rob)
>
> ---------- Forwarded message ----------
> From: rob levy <r.p.l...@gmail.com>
> Date: Sun, Jun 20, 2010 at 5:48 PM
> Subject: Re: [agi] An alternative plan to discover self-organization theory
> To: agi@v2.listbox.com
>
>
> On a related note, what is everyone's opinion on why evolutionary
> algorithms are such a miserable failure as "creative machines", despite
> their successes in narrow optimization problems?
>
> I don't want to conflate the possibly separable problems of biological
> development and evolution, though they are interrelated. There are various
> approaches to evolutionary theory such as Lima de Faria's "evolution without
> selection" ideas and Reid's "evolution by natural experiment" that suggest
> natural selection is not all it's cracked up to be, and that the step of
> generating, ("mutating", combining, ....) is where the more interesting
> stuff happens. Most of the alternatives to Neodarwinian Synthesis I have
> seen are based in dynamic models of emergence in complex systems. The upshot
> is, you don't get creativity for free, you actually still need to solve a
> problem that is as hard as AGI in order to get creativity for free.
>
> So, you would need to solve the AGI-hard problem of evolution and
> development of life, in order to then solve AGI itself (reminds me of the
> old SNL sketch: "first, get a million dollars..."). Also, my hunch is that
> there is quite a bit of overlap between the solutions to the two problems.
>
> Rob
>
> Disclaimer: I'm discussing things above that I'm not and don't claim to be
> an expert in, but from what I have seen so far on this list, that should be
> alright. AGI is by its nature very multidisciplinary which necessitates
> often being breadth-first, and therefore shallow in some areas.
>
>
> On Sun, Jun 20, 2010 at 2:06 AM, Steve Richfield <
> steve.richfi...@gmail.com> wrote:
>
>> No, I haven't been smokin' any wacky tobacy. Instead, I was having a long
>> talk with my son Eddie, about self-organization theory. This is
>> *his*proposal:
>>
>> He suggested that I construct a "simple" NN that couldn't work without
>> self organizing, and make dozens/hundreds of different neuron and synapse
>> operational characteristics selectable ala genetic programming, put it on
>> the fastest computer I could get my hands on, turn it loose trying arbitrary
>> combinations of characteristics, and see what the "winning" combination
>> turns out to be. Then, armed with that knowledge, refine the genetic
>> characteristics and do it again, and iterate until it *efficiently* self
>> organizes. This might go on for months, but self-organization theory might
>> just emerge from such an effort. I had a bunch of objections to his
>> approach, e.g.
>>
>> Q. What if it needs something REALLY strange to work?
>> A. Who better than you to come up with a long list of really strange
>> functionality?
>>
>> Q. There are at least hundreds of bits in the "genome".
>> A. Try combinations in pseudo-random order, with each bit getting
>> asserted in ~half of the tests. If/when you stumble onto a combination that
>> sort of works, switch to varying the bits one-at-a-time, and iterate in this
>> way until the best combination is found.
>>
>> Q. Where are we if this just burns electricity for a few months and finds
>> nothing?
>> A. Print out the best combination, break out the wacky tobacy, and come
>> up with even better/crazier parameters to test.
>>
>> I have never written a line of genetic programming, but I know that others
>> here have. Perhaps you could bring some rationality to this discussion?
>>
>> What would be a "simple" NN that needs self-organization? Maybe a small
>> "pot" of neurons that could only work if they were organized into layers,
>> e.g. a simple 64-neuron system that would work as a 4x4x4-layer visual
>> recognition system, given the input that I fed it?
>>
>> Any thoughts on how to "score" partial successes?
>>
>> Has anyone tried anything like this in the past?
>>
>> Is anyone here crazy enough to want to help with such an effort?
>>
>> This Monte Carlo approach might just be simple enough to work, and simple
>> enough that it just HAS to be tried.
>>
>> All thoughts, stones, and rotten fruit will be gratefully appreciated.
>>
>> Thanks in advance.
>>
>> Steve
>>
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