Mike Novack wrote:
...the LOGIC of what you are saying. If there is a function, which given a board position returns the best next move and there is a second function, which given a board position returns the pair of values, the best next move and what color your underwear is (pick anything) WHY do you say the second function would play stronger go?
i didn't say that.
i couldn't decide whether you genuinely don't follow the logic of my argument, or are just winding me up (ie, trolling).
So i googled you but could only find your comments on other topics in this forum, which led me to believe that i should give you the benefit of the doubt and assume it is the former case.
So here is my attempt to explain my argument:
Master Alphago's technique is the best we know of, so far. But that doesn't mean she is the best that could ever be made, even if no human could ever beat her.
So the questions facing everyone interested in AI are these:
1. what could be better?
2. what does DCNN+Monte's success tell us about the intellectual challenge of Go?
last year i mused upon the second question in comments on YouTube videos of the Alphago - Lee Sedol match.
As to the first question, i don't have an unequivocal answer, but i did make a suggestion (CG) for future research last year, which included testing a simulated CG on just one example - the only example i know of where Alphago made a game-losing move. I was pleasantly surprised that CG quickly found a move that as far as i could see was better than the move Alphago made - it was a variation of the defence to Lee's wedge that Myungwan Kim found.
By itself, that doesn't prove anything, but it is a suggestive evidence.
Since then, DeepMind have said that they have improved Alphago so she wouldn't make the same mistake again in the same situation.
So nothing can be said for sure as to the relative playing strengths of DCNN and deductive logic. It would, however, be easy to test: simply replace Master's DCNN move generator with CG's, and her evaluation DCNN with CG's estimation function, and using all the rest of Master's paraphernalia (parallel Monte search on gerzillions of processors), see what happens when they face each other.
Only DeepMind could do that test, but a pimply kid with a PC could do a simpler and cheaper mini-test: implement Alpha's published algorithms as one program and CG's as another and let them battle it out on the same hardware. My adolescence finished half a century ago, and the rest of my life is too short, so i won't be that pimply kid.
As to the fact that CG can SWIM, i never claimed that that implies its thinking is superior to any other technique - that was your own illogical inference.
That it can, merely demonstrates that its way of thinking is comprehensible to people in terms that they can understand. If its thinking is reasonable, then it could be a useful learning aide.
Please note that i am using the term "thinking" in its Turing sense; i do not claim that CG's thinking is isomorphic to human thinking. Indeed, i have sometimes tried to apply CG's methods in my own games, and have sometimes discovered a move that was better than the one which had first come to my mind. But i am a weak player, so that doesn't mean anything - it's merely an indoor recreation.