Le 21/11/2017 à 23:27, "Ingo Althöfer" a écrit : > Hi Erik, > >> No need for AlphaGo hardware to find out; any >> toy problem will suffice to explore different >> initialization schemes... > I know that. > > My intention with the question is a different one: > I am thinking how humans are learning. Is it beneficial > to have learnt related - but different - stuff before? > The answer will depend on the case, of course. > > And in my role as a voyeur, I want to understand if having > learnt a Go variant X before turning my interest to a > "slightly" different Go variant Y. Do, I want to combine > the subject with some entertaining learning process. > (For instance, looking at the AlphaGo Zero games from the > 72 h experiment in steps of 2 hours was not only insightful > but also entertaining.) > >> you typically want to start with small weights so >> that the initial mapping is relatively smooth. > But again: For instance, when a eight year old child starts > to play violin, is it helpful or not when it had played > say a trumpet before? I believe that Human brain is too far from the alphago neural network that one knowledge about one can be transfered to the other. > My understanding is that the AlphaGo hardware is standing > somewhere in London, idle and waitung for new action... Definitely not idle: “[They] needed the computers for something else.”
source: https://techcrunch.com/2017/11/02/deepmind-has-yet-to-find-out-how-smart-its-alphago-zero-ai-could-be/ > Ingo. > > _______________________________________________ > 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
