I do not regard chess as important as a drosophila for AI. It would just be
a first milestone where we can make a fast proof of concept for an AGI
approach. The faster we can sort out bad AGI approaches the sooner we will
obtain a successful one.

 

Chess has the advantage to be an easy programmable domain.

The domain of chess is not AGI-complete but crucial problems for AGI can be
found in chess as well.

AGI can be trained automatically against strong chess programs because those
engines offer an open API.

The performance can be evaluated by elo-ranking, i.e. a common evaluation
algorithm for chess players

 

But I do not emphasize performance evaluation too much. The milestone would
be passed successfully if the AGI would use a current PC and would be able
to beat average human chess players after it has played many thousand chess
games against chess programs.

 

It would be a big step towards AGI if someone could build a chess playing
program by a learning software which is pattern based and is not inherently
build for chess.

 

I think such a program would gain much attention in the community of AI
which is also necessary to accelerate the research of AGI.

Of course successful experiments with embodiment would probably gain more
attention. But the development cycle from concept to experiment would take
much longer time with embodiment than with an easy to program and
automatically testable chess domain. 

 

We should suspect that we still have to go many times through this cycle and
therefore it is essential that the cycle should need as few efforts and time
as possible.

 

- Matthias

 

 

Vladimir Nesov [mailto:[EMAIL PROTECTED] wrote



Current AIs learn chess without engaging in social activities ;-).

And chess might be a good drosophila for AI, if it's treated as such (

http://www-formal.stanford.edu/jmc/chess.html ).

This was uncalled for.

 




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agi
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