What Linas is saying, I think, is that to get a complex multi-component learning system like OpenCog to work, there are many complex "tuning /adapting" tasks to be done.... Each time you want to apply a certain learning algorithm to a certain sort of problem (such as, the problem of helping another learning algorithm do its stuff better), you have to tweak that learning algorithm in certain ways. He's afraid that, in a system based on the interactions of a lot of different learning algorithms for a lot of different purposes, this leads to a very large number of moderately-complex algorithm tuning/adaptation problems.
So he's saying: If we had a "meta-learning" method for automatically tuning/adapting a learning algorithm to a new domain and a new sort of problem, *then* an architecture like OpenCog could be made to work a lot more tractably. Otherwise, getting it to work is gonna be a long slog of tuning/tweaking each component for its interaction with each other component. At least, that's my quick gloss of his point. I'm unsure of my reaction. Indeed, metacognition is important -- as Linas knows, Nil and I worked on a DARPA-funded project on meta-learning last year. (We have an in-progress paper on "meta-learning for feature selection" in a MOSES context.) On the other hand, the human brain was honed incrementally by evolution over a long period of time, and evolution is exactly the sort of algorithm that is able to repetitively carry out the long slog of tuning/tweaking each component of a complex system for its interaction with each other component... Ultimately, I think we can build an OpenCog thinking machine without this kind of metalearning he alludes to. BUT ... absolutely, the further we can go in that direction the better... ben g On Tue, Sep 25, 2012 at 9:52 PM, Piaget Modeler <[email protected]>wrote: > > Kindly advise, which component is "The Magic Happens Here"? I didn't > recognize it on Ben's diagram or mine. > > > https://www.facebook.com/photo.php?fbid=460040220684646&set=a.217364258285578.55073.203359906352680&type=1&theater > > > Please advise. > > ~PM. > > > ------------------------------ > From: [email protected] > Date: Tue, 25 Sep 2012 20:44:11 -0500 > Subject: [agi] Magic Happens Here [was Re: [opencog-dev] Uber big scary > monster OpenCog diagram > To: [email protected] > CC: [email protected]; [email protected] > > > > > On 12 September 2012 15:36, Ben Goertzel <[email protected]> wrote: > > > http://goertzel.org/WholeBigOpenCogDiagram.pdf > > > So I got to thinking about the "Magic Happens Here" part of the diagram, > and I think maybe it got left out of the diagram. > > So, for example, I was recently thinking that I could use MOSES to > automatically learn new link-grammar parse relations. Now, it doesn't > explicitly have to be MOSES that would do the learning; I suppose that many > modern-day, reasonably competent learning systems might do the trick: they > would need only to be able to do some basic modelling of the innards of a > black box. And it doesn't have to be link-grammar either: some other > reasonably flexible NLP system would do. > > As it became clear as to how to hook these two up, so as to learn new > rules, I also thought about what it couldn't do ... and realized that I'd > need some other variants and modifications to handle those cases. So, my > plan went from hooking up the two things, to realizing that I would need to > hook them up in three distinct ways. Each different way handles a certain > generic kind of learning problem, but with a different focus and a > different output/outcome. And I started grasping that in fact, maybe > there are 4 or 5 or 6 different other situations to deal with. > > And at that point, it gets out of hand -- all of a sudden, I need to > manually handle a bunch of different learning tasks. Each task may take > months to code up and make operational. And what if there are more than 6? > That's when I realized that, in fact, I have a meta-learning problem. > That is, what I really need is a system that can learn how to learn > specific learning tasks. *That* is the "Magic happens Here" bubble. > > At the moment, I have no clue how to do this meta-learning. But I do know > where to start: experimental trial and error. Go ahead, hook up moses to > link-grammar. See what happens. Plug the holes, See if a general pattern or > paradigm emerges. If, after much work, some meta-pattern becomes apparent, > then, well, that was the magic part. After that .. who knows. But one > cannot find out, until one starts trying to build these things. > > --linas > *AGI* | Archives <https://www.listbox.com/member/archive/303/=now> > <https://www.listbox.com/member/archive/rss/303/19999924-5cfde295> | > Modify<https://www.listbox.com/member/?&;>Your Subscription > <http://www.listbox.com> > -- Ben Goertzel, PhD http://goertzel.org "My humanity is a constant self-overcoming" -- Friedrich Nietzsche ------------------------------------------- AGI Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/21088071-c97d2393 Modify Your Subscription: https://www.listbox.com/member/?member_id=21088071&id_secret=21088071-2484a968 Powered by Listbox: http://www.listbox.com
