The games look like previously published ones. Just repeating? Hideki
mic: <31fa8de6-c157-5de6-78fb-a66e6957a...@gmx.de>: >There are several AlphaGo instances playing against each other on Tygem >at this moment. >-Michael. > >On 21.10.2017 14:21, David Ongaro wrote: >> Am 10/21/2017 um 03:12 AM schrieb uurtamo .: >> >>> This sounds like a nice idea that is a misguided project. >>> >>> [...] >>> Just accept that something awesome happened and that studying those >>> things that make it work well are more interesting than translating >>> coefficients into a bad understanding for people. >>> >>> I'm sorry that this NN can't teach anyone how to be a better player >>> through anything other than kicking their ass, but it wasn't built for >>> that. >> >> Roberts approach might be misguided, but I don't agree that having the >> raw network data couldn't teach us something. E.g. have a look at this >> guy who was able to identify the neurons responsible for generating URLs >> in a wikipedia text generating RNN: >> >http://karpathy.github.io/2015/05/21/rnn-effectiveness/#visualizing-the-predictions-and-the-neuron-firings-in-the-rnn. >> >> E.g. it might be possible to find the network Part of AlphaGo Zero which >> is responsible for L&D problems and use it to dream up new Problems! The >> possibilities could be endless. This kind of research might have been >> easier with the "classic" AlphaGo with separated policy and value >> networks, but should be possible anyways. >> >> Also lets not forget DeepMinds own substantial research in this area: >> https://deepmind.com/blog/cognitive-psychology/. >> >> I understand that DeepMind might be unable to release the source code of >> AlphaGo due to policy or licensing reasons, but it would be great (and >> probably much more valuable) if they could release the fully trained >> network. As Gian-Carlo Pascutto has pointed out, replicating this would >> not only incur high hardware costs but also take a long time. >> >> David O. >> >> >>> On Fri, Oct 20, 2017 at 8:24 AM, Robert Jasiek <jas...@snafu.de >>> <mailto:jas...@snafu.de>> wrote: >>> >>> On 20.10.2017 15:07, adrian.b.rob...@gmail.com >>> <mailto:adrian.b.rob...@gmail.com> wrote: >>> >>> 1) Where is the semantic translation of the neural net to >>> human theory >>> knowledge? >>> >>> As far as (1), if we could do it, it would mean we could >>> relate the >>> structures embedded in the net's weight patterns to some other >>> domain -- >>> >>> >>> The other domain can be "human go theory". It has various forms, >>> from informal via textbook to mathematically proven. Sure, it is >>> also incomplete but it can cope with additions. >>> >>> The neural net's weights and whatnot are given. This raw data can >>> be deciphered in principle. By humans, algorithms or a combination. >>> >>> You do not know where to start? Why, that is easy: test! Modify >>> ONE weight and study its effect on ONE aspect of human go theory, >>> such as the occurrance (frequency) of independent life. No effect? >>> Increase the modification, test a different weight, test a subset >>> of adjacent weights etc. It has been possible to study semantics >>> of parts of DNA, e.g., from differences related to illnesses. >>> Modifications on the weights is like creating causes for illnesses >>> (or improved health). >>> >>> There is no "we cannot do it", but maybe there is too much >>> required effort for it to be financially worthwhile for the "too >>> specialised" case of Go? As I say, a mathematical proof of a >>> complete solution of Go will occur before AI playing perfectly;) >>> >>> So far neural >>> nets have been trained and applied within single domains, and >any >>> "generalization" means within that domain. >>> >>> >>> Yes. >>> >>> -- >>> robert jasiek >>> >>> _______________________________________________ >>> Computer-go mailing list >>> Computer-go@computer-go.org <mailto:Computer-go@computer-go.org> >>> http://computer-go.org/mailman/listinfo/computer-go >>> <http://computer-go.org/mailman/listinfo/computer-go> >>> >>> >>> >>> >>> _______________________________________________ >>> Computer-go mailing list >>> Computer-go@computer-go.org >>> http://computer-go.org/mailman/listinfo/computer-go >> >> >> >> _______________________________________________ >> Computer-go mailing list >> Computer-go@computer-go.org >> http://computer-go.org/mailman/listinfo/computer-go >> > >--- >Diese E-Mail wurde von Avast Antivirus-Software auf Viren geprüft. >https://www.avast.com/antivirus > >_______________________________________________ >Computer-go mailing list >Computer-go@computer-go.org >http://computer-go.org/mailman/listinfo/computer-go -- Hideki Kato <mailto:hideki_ka...@ybb.ne.jp> _______________________________________________ Computer-go mailing list Computer-go@computer-go.org http://computer-go.org/mailman/listinfo/computer-go
