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I agree. There are many interesting questions Deep Mind could have answered about both go and chess. I am still bitter they didn't take a few days more to run e
by bluecalm 7y ago
I agree. There are many interesting questions Deep Mind could have answered about both go and chess.
I am still bitter they didn't take a few days more to run experiments of great interest for fans of both games. For chess the simplest one would be to take most popular positions from top level human play and let A0 play Stockfish from that (say 10 times from every of 100 positions). Then do the same for self-play and then most importantly publish all the games not selected sample.
They kinda did something similar but the positions they selected were chosen for entertainment value. We still don't know how Alpha Zero plays from positions that are actually interesting for human players.
- monkeypizza 7y agoOpen source research is continuing. There are a few open source implementations of the alphago algorithm and some new work being done to improve it for go. Check out lizzie, which is a nice front end to leela zero. https://lifein19x19.com/viewtopic.php?f=10&t=17095 https://lifein19x19.com/viewtopic.php?f=10&t=17095