Author: Bas Hamstra
Date: 14:36:55 01/05/01
I would like to share experience with some that have tried Temporal Difference learning. Currently one of the problems I see is that for example BISHOPMOBILITY has very large partial derivatives. So the updates for this term swing wildly and distort learning. On the other hand, if I reduce the learning factor to bring this in proportion, a term like DOUBLEDPAWN won't ever get to a realistic value. One way to do better is to work with derivatives -1 or +1 only, depending on if the partial derivative for a term is above or below zero. This results in a tendency to realistic values for most terms. Still, a few terms refuse to show a "trend" at all, or even the wrong trend. Are others having this problems? (To see what is going on I showed the developments of the weights in a graph, to verify it does something useful, best results so far with -1/+1 only, bad results when using the real derivatives) Regards, Bas.
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