Author: Graham Laight
Date: 18:35:02 06/22/00
When we've discussed NNs in the past, as far as I remember (and excuse me if I've missed some threads where this has already been discussed), we've always discussed them in terms of creating one giant, monolithic NN. In a flash of inspiration last night, it suddenly occured to me that what you actually need is one NN for each type of "positional factor" you are trying to recognise. For example, you could build a NN of an appropriate size, and train it to look out for cases where a "smothered mate" was likely to become possible - using a set of positions where it either is, or isn't likely. Then, for each node that is to be evaluated in a game, you can pass that position to this NN, and come up with an assessment of whether this particular positional weakness (or strength!) exists. When you have got 50,000 such NNs working, then "vous voila!" - you have your player with grandmaster level skill. I think that this would be a good use for multiple processor (or multiple computer) systems. And, in reality, wouldn't it be a good model for how the human brain works? In summary, instead of thinking about one big NN, think about having lots of little NNs to play chess with. -g
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