Hi, lately a friend and me wondered about the following idea.
Let's assume you have a reasonably strong move prediction DCNN. What happens if you now train a second net on the same database. When training the first net, you tried to maximize the judgement value of the expert move. But for the second net you now try to maximize the maximum of the judgement of both nets. This means, that the second net does not profit from finding moves the first net can easily find, but instead will try to fill in the weaknesses of the first net. In practical application the easy static usage would be to first expand the top2 candidates of the first net, then mix in the top candidate of the second net, then again the next 2 candidates from the first net, etc. What do you guys think about that? Cheers, Marc _______________________________________________ Computer-go mailing list Computer-go@computer-go.org http://computer-go.org/mailman/listinfo/computer-go
