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Subject: Temporal Difference

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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