From: Ben Goertzel (firstname.lastname@example.org)
Date: Mon Oct 24 2005 - 15:47:58 MDT
It's true that making an AGI, given current software technology, is a big
pain, and it takes a long time to get from vision to implementation.
I agree that better software tools would help make the process a lot easier,
even though I have a feeling your vision of better software tools is a bit
However, I have chosen to focus on AGI itself rather than on building better
tools, because I've judged that given my limited resources, I'll probably
get to AGI faster via focusing on AGI than via focusing on tools first.
While tools work is conceptually easier than AGI work by far, it still
requires a lot of thought and a lot of manpower.
I would be more interested in your tools ideas if they were presented in a
more concrete way.
-- Ben G
> -----Original Message-----
> From: email@example.com [mailto:firstname.lastname@example.org]On Behalf Of Michael
> Sent: Monday, October 24, 2005 5:39 PM
> To: email@example.com
> Subject: Re: Loosemore's Proposal
> Richard Loosemore wrote:
> >> This is a gross simplification, but basically this just means that
> >> AGIs amenable to formal verification will resemble software systems
> >> more than organic systems. It is intuitively apparent (and this is
> >> a case where intuition is actually right) that since computers are
> >> designed to support formal software systems, not organic simulations,
> >> this approach will also make more efficient use of currently
> >> available hardware.
> > That is not what I said.
> No, but it's what your assertion implies.
> > Not a straw man: you yourselves are taking the "logic" approach that I
> > am talking about. Until you understand that, you are missing the point
> > of this entire argument.
> The scope of 'yourselves' is unclear, but I certainly don't take
> the position you're attempting to dismiss.
> > Stop trying to deflect attention to some other group: I am talking
> > about you and your approach.
> You may be talking about me, but you are not describing my approach.
> > Nonsense: LOGI hasn't solved the grounding problem.
> True, but it does propose a solution in abstract, albeit without
> much constructive detail. My point wasn't that the problem has been
> conclusively solved, it hasn't, my point was that most researchers
> are well aware of the problem and there have been several credible
> attempts to solve it (most of which await experimental verification).
> > Cite one example of systematic variation of local mechanisms in
> > AGI systems, in search of stability. There is not one. Nobody has
> > tried the approach that I have adopted, so why, in your book, is it not
> > novel?
> Plenty of researchers have tried a large number of local dynamics in
> their system. Lenat's Eurisko project is a good example; he tried
> hundreds of different hand-created heuristics and numerous structural
> features in a search for a system that would work. This is usually
> what happens when a system is built and fails to live up to initial
> expectations; researchers fall back on trial and error. Eurisko is
> actually a good example of a combination of manual and automated
> trial-and-error; the system itself was a self-modifying design full
> of semi-specialised 'local dynamics', with Lenat providing high
> level guidance and the system itself doing local exploration of the
> design landscape in each revision. I admitt that I am unclear as
> to how you intend to direct your design space exploration.
> > So, where else is there a development environment that would easily
> > allow someone who was not a hacker to produce 100 different
> *designs* of
> > cognitive systems, using different local mechanisms, then feed them the
> > same sets of environmental data, then analyse the internal dynamics and
> > make side by side comparisons of the behavior of those 100 systems, and
> > get all this done in a week, so you can go on to look at another set of
> > 100 systems next week?
> I don't see how you can bypass fundemental limits on how quickly humans
> can invent and input design complexity. Incremental improvements are
> possible with a lot of work, but if you seriously expect to try 100
> designs in a week they will need either very simple specifications or
> will be very similar. This translates into either a very low resolution
> search (if you used some kind of expression system to translate simple
> specs into functional systems) or a very slow search of an extremely
> large design space. This kind of thing could work if intelligence was
> truely modularisable, you had all the essential modules predeveloped
> and you were just looking for the correct way to connect them, but even
> if that was possible it just pushes all the hard work into specifying
> and building the 'adequate set' of modules.
> > If I am not talking about you, when was the last time you built a
> > complete AGI and tested it to see if the local mechanisms you chose
> > rendered it stable (a) in the face of real world environmental
> > interaction and (b) in the course of learning?
> I haven't done this of course (yet; I'm working on it), but I can't
> see how you can possibly apply this as a research standard. /No one/
> has built a complete AGI yet, and past attempts to do so have taken
> years or decades. It's hard even to find someone who will admitt that
> they tried and failed; usually people say that they had to abandon
> their projects due to lack of time/money/staff, or maintain that just
> a few more years work should crack it.
> >> This part does not appear unreasonable; it seems similar to the
> >> 'experimental investigation of AGI goal system dynamics' that Ben
> >> has historically been in favour of.
> > You have never got anywhere near trying it
> How do you know this? You don't, of course. Actually I have got
> about as close to trying this sort of experiment as one can get
> without embarking on a multi-year implementation project. I've
> done a fair bit of exploratory implementation covering a
> reasonably diverse range of basic architectures, of which the
> problem solver based on enhanced genetic algorithms probably came
> the closest to your sensibilities, though obviously the design
> complexity of anything that can be implemented in a couple of
> months is sharply bounded and well below what you'd need for an
> > First-principles research in FAI? You don't have a workable
> > theory of FAI, you just have some armchair speculation.
> I don't have such a theory nor am I working on one. But formal
> theories of this calibre do not pop out of the ether fully
> formed. They are the result of years of hard work on a progressive
> series of precursors, which I /can/ observe the SIAI steadily
> making progress on. I expect that you would write off the entire
> field of theoretical physics as useless 'armchair speculation', or
> at least you would if you could find a way to ignore the successes
> of that discipline.
> * Michael Wilson
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