It depends what "to play chess poorly" mean. No one would expect that a
general AGI architecture can outperform special chess programs with the same
computational resources. I think you could convince a lot of people if you
demonstrate that your approach which is obviously completely different from
brute force chess can learn chess to a moderate level of a let's say average
10 year old human chess player.
At least when you are in your open cog roadmap between phase "artificial
child" and "artificial adult" then your system should necessarily be able
to learn chess without any special hacking of hidden chess knowledge.
BTW, Computer GO is already not so bad:
<http://www.engadget.com/2008/08/15/supercomputer-huygens-beats-go-professio
nal-no-one-is-safe/>
http://www.engadget.com/2008/08/15/supercomputer-huygens-beats-go-profession
al-no-one-is-safe/
- Matthias
Ben wrote:
I strongly suspect that OpenCog ... once more of the NM tools are ported to
it (e.g. the completion of the backward chainer port) ... could learn to
play chess legally but not very well. To get it to play really well would
probably require either a lot of specialized hacking with inference control,
or a broader AGI approach going beyond the chess domain... or a lot more
advancement of the learning mechanisms (along lines already specified in the
OCP design).... To me, teaching OpenCog to play chess poorly would prove
almost nothing. And getting it to play chess well via tailoring the
inference control mechanisms would prove little that's relevant to AGI,
though it would be cool.
Ok. I do not say that your approach is wrong. In fact I think it is very
interesting and ambitious. But as you think that my approach is not the best
one I think that your approach is not the best one. Probably, the
discussion could be endless. And probably you already have invested too much
effort in your approach that you really can consider to change it. I hope
you are right because I would be very happy to see the first AGI soon,
regardless who will build it and regardless which concept is used.
I would change my approach if I thought there were a better one. But you
haven't convinced me, just as I haven't convinced you ;-)
Anyway, to take your approach I would not need to change my AGI design at
all: OCP could be pursued in the domain of learning to play chess. I just
don't think that's the best choice.
BTW, if I were going to pursue a board game I'd choose Go not chess ... at
least it hasn't been solved by narrow-AI very well yet ... so a really good
OpenCog-based Go program would have more sex appeal ... there has not been a
Deep Blue of Go
My son is a good Go player so maybe I'll talk him into trying this one day
;-)
ben g
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