Hi,

I now see that I have not updated this question with the answer. It turned out that my input vectors were 'too random'. The use case was to train a neural network on a number of international draughts positions. If you choose a collection of randomly generated legal positions (a question also is if these positions could be reached at all from the starting position BTW) as the training set the neural network cannot 'find' a relation between the positions and the result (won/draw/lost), so the neural network just predicts the average score (draw). However, if you generate a collection of 'reasonably random' positions by playing a number of games selecting 'reasonable random' moves (so moves that do not immediately loose a man for example) the network starts to 'see' a relation between the positions and the result, and the network predicts about 80-90% of the results correctly.

Regards, GW