Then again DNNs also manage feature extraction on unlabeled data with increasing levels of abstraction towards upper layers. Perhaps one could apply such a specifically trained DNN to artificial board situations that emphasize specific concepts and examine the network's activation, trying to map activation patterns to human Go concepts.
Still hard work, and questionable payoff, but just wanted to pitch that in as idea. > However, if someone was to do all the dirty work setting up all the > infrastructure, hunt down the training data and then financially facilitate > the thousands of hours of human work and the tens to hundreds of thousands > of hours of automated learning work, I would become substantially more > interested...and think a high quality desired outcome remains a low > probability. _______________________________________________ Computer-go mailing list Computer-go@computer-go.org http://computer-go.org/mailman/listinfo/computer-go
