This is indeed interesting, however I think it is a lot of work.... The problem is that you have to recode a lot of things. First of all the the move generator. Then the bearoff evaluator must be reconstructed. I guess you can use the same system as in one side bearoff databases, (where you keep the a table of the #-rolls-to-get-all-off distribution for every position), but it has to take the bearoff rules into account. Makes the distributions different. This makes a difference also for race positions as well, so the race network must be retrained as well.... I guess you can make a simple TD(lambda) training of a neural net when all that's in place.
So, challenging that it would be cool to try, however I think I rather spend my time on other projects... Hmmmm... it isn't that much changes..... maybe I should at least take a deeper look. -Øystein
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