Hi Shane, I understand your perspective and I think it's a reasonable one.
I think that what you'll get from this approach, if you're lucky, is a kind of "primitive brain", suitable to control something with general intelligence around that of a reptile or a very stupid mammal. Then, you can use the structures/dynamics of this primitive brain as raw materials, for constructing a more powerful general intelligence. I think that a realistic general intelligence has got to consist of a set of components, each carrying out specialized functions but based on the same essential knowledge-representation and learning dynamics. Each of these specialized components embodies a certain in-built "inductive bias" which guides the learning dynamics within it. In this context, I think your experiments may be useful in exploring the space of plausible "essential knowledge-representation and learning dynamics." I think that Novamente already has a decent knowledge-rep/learning-dyn core (based on probabilistic combinatory term logic, probabilsitic inference and evolutionary learning), but I also think there are LOTS of other choices to make. I convinced myself a while ago that a variant of hebbian neural nets could do the trick as well, although with much less efficiency. maybe via your evolutionary method you could discover something even more wonderful ;-) -- Ben g > I agree totally. Indeed I advocate going further and actually evolving > the fundamental structures and dynamics that drive the system --- > designing > them by hand or trying to prove any useful results about what happens in > a complex recurrent network seems to be really difficult. Thus perhaps a > combination of artificial evolution, experimentation, and the development > of theories to explain what we see is the most likely approach to succeed. > At least that's my best guess at the moment based on what I've > seen working > on various AI/AGI projects in the past. > > I sent Ben an email along similar lines a few days back describing my > own little (extremely slowly moving and incomplete) set of AGI ideas that > I refer to as the vetta project. I've pasted part of what I wrote below > for anybody who is interested. > > Cheers > Shane > > ----------------------------------------------------------------------- > > > Well it's a mix of things really --- and it changes over time a bit too! > > Basically my approach goes something like this: > > 1) Build a set of precise "IQ" tests for machines. These tests cover > everything from bacteria level intelligence to super human > intelligence. > It's a reasonably complex web of relations: passive > predictors, classifiers, > simple reactive systems, Markov chains, MDPs, POMDPs and many > others..... > You can prove a whole bunch of relations between all these > mathematically, > indeed that's what I did for the first 4 months of my PhD. > That's the first > step; however it doesn't really capture how difficult a > problem is. So for > that you need something like like complexity theory (both > time and space). > Anyway, the point is that you can then measure exactly where > in this complex > tree of abilities an AGI system is. The most general form of > this is what > I call "cybernance" and is closely related to the "intelligence order > relation" that appears in the AIXI proofs. > > 2) Define a space of systems that should contain an AGI. This is > a bit harder > to explain. Again complexity theory comes into it. So > things like the > fact that I think that the "meta logic" of a system has to be > very small > and thus the building blocks of the system must be quite > simple. Also that > the processing of the system must have certain > self-organizing properties > such as compression of information in space and time, > consistency over levels > of abstraction and stuff like that. This is the more > philosophical part I > suppose. The point is that I need to make this space of > possible systems > as small as I can without making a mistake and excluding a > working design > for an AGI from the set. Oh, and I should mention that I'm > thinking of > some kind of information processing network here: some kind > of neural network, > Hebbian network, HMM, Bayesian network. Basically the space > is a super set > of all these things and more. > > 3) Genetic programming. (1) gives us a fine grained > multi-objective fitness > function and (2) defines a search space. Now I can't just > run my GA and > expect things to work here! Clearly the space in (2) is > going to be pretty > large. So at this point it becomes a bit of an experimental > science and I > have to mix things around a bit. So I'll be restricting the > tests to just > certain very simple objectives and restricting the space to > smaller subspaces > to see what works and what doesn't. Then try to cross over > solutions to find > systems that work for both etc. Hopefully at this stage I > can zero in on > promising parts of the space of possible designs. Perhaps > even design my > own attempts at functioning systems and throw them into the > evolutionary mix > and see if they can breed with other different partial > solutions to form > new and interesting things. > > I guess in a sense it's the natural evolution of intelligence but > on steroids: > rather than having fitness related to intelligence very > indirectly via survival > here we measure a kind of computational intelligence very > direction and equate it > with survival. Also we restrict the space of possible designs as > much as we can > get away with to speed things up --- this is the theory side of > the design I > suppose. > > So the big question then is: Can I make the theory strong enough > to make the > search space small enough so that I can make the series of very > tiny little > steps needed to go from a near zero level of intelligence up to high level > intelligence? > > Well, at least that's a one page summary of the basic nature of > the approach. > Hopefully it gives you some idea of what I'm thinking. > > As for the name "vetta", in case you ever wondered. In Sanskrit it means, > "one who has knowledge". However in Italian it also means > "summit" or "peak" > which is a reference of course to the the climbing of the GA > solutions toward > the peak of the fitness function, i.e. cybernance. > > ------- > To unsubscribe, change your address, or temporarily deactivate > your subscription, > please go to http://v2.listbox.com/member/[EMAIL PROTECTED] > ------- To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/[EMAIL PROTECTED]
