Re: [Computer-go] UEC cup 2nd day

I have used TensorFlow to train a CNN that predicts the next move, with a similar architecture to what others have used (1 layers of 5x5 convolutions followed by 10 more layers of 3x3 convolutions, with 192 hidden units per layer and ReLU activation functions) but with much simpler inputs. I found

Re: [Computer-go] UEC cup 2nd day

Thanks for the very interesting replies, David, and Remi. No-one is using TensorFlow, then? Any reason not to? (I'm just curious because there looks to be a good Udacity DNN course (https://www.udacity.com/course/deep-learning--ud730), which I was considering, but it is using TensorFlow.) Remi

Re: [Computer-go] *****SPAM***** Re: UEC cup 2nd day

Which one is Remi's? On Thu, Mar 24, 2016 at 1:09 AM, David Fotland wrote: > There was one program (Shrike) that had a dnn without search. It didn’t > finish in the top 8. Zen and Crazystone have custom DNN implementations. > Dark Forest uses Torch. The rest used

Re: [Computer-go] UEC cup 2nd day

Hi, This UEC Cup was really very exciting. I had started to code my own home-made deep learning library in November, after finishing my Japanese mahjong engine. I was working quietly on it when the Alphago paper was published. Then I felt that I had to urgently get something to work before

Re: [Computer-go] *****SPAM***** Re: UEC cup 2nd day

There was one program (Shrike) that had a dnn without search. It didn’t finish in the top 8. Zen and Crazystone have custom DNN implementations. Dark Forest uses Torch. The rest used Caffe. Remi's implementation is unusual and interesting. I'll let him share it if he wants to. David >