This would be very similar to the integration I do in Many Faces of Go. The old engine provides a bias to move selection in the tree, but the old engine is single threaded and only does a few hundred evaluations per second. I typically get between 40 and 200 playouts through a node before Old Many Faces adjusts the biases.
David > -----Original Message----- > From: Computer-go [mailto:computer-go-boun...@computer-go.org] On Behalf > Of Mark Wagner > Sent: Saturday, December 20, 2014 11:18 AM > To: computer-go@computer-go.org > Subject: Re: [Computer-go] Move Evaluation in Go Using Deep Convolutional > Neural Networks > > Thanks for sharing. I'm intrigued by your strategy for integrating with > MCTS. It's clear that latency is a challenge for integration. Do you have > any statistics on how many searches new nodes had been through by the time > the predictor comes back with an estimation? Did you try any prefetching > techniques? Because the CNN will guide much of the search at the frontier > of the tree, prefetching should be tractable. > > Did you do any comparisons between your MCTS with and w/o CNN? That's the > direction that many of us will be attempting over the next few months it > seems :) > > - Mark > > On Sat, Dec 20, 2014 at 10:43 AM, lvaro Begu <alvaro.be...@gmail.com> > wrote: > > If you start with a 19x19 grid and you take convolutional filters of > > size > > 5x5 (as an example), you'll end up with a board of size 15x15, because > > a 5x5 box can be placed inside a 19x19 board in 15x15 different > > locations. We can get 19x19 outputs if we allow the 5x5 box to be > > centered on any point, but then you need to do multiply by values > outside of the original 19x19 board. > > Zero-padding just means you'll use 0 as the value coming from outside > > the board. You can either prepare a 23x23 matrix with two rows of > > zeros along the edges, or you can just keep the 19x19 input and do > > your math carefully so terms outside the board are ignored. > > > > > > > > On Sat, Dec 20, 2014 at 12:01 PM, Detlef Schmicker <d...@physik.de> > wrote: > >> > >> Hi, > >> > >> I am still fighting with the NN slang, but why do you zero-padd the > >> output (page 3: 4 Architecture & Training)? > >> > >> From all I read up to now, most are zero-padding the input to make > >> the output fit 19x19?! > >> > >> Thanks for the great work > >> > >> Detlef > >> > >> Am Freitag, den 19.12.2014, 23:17 +0000 schrieb Aja Huang: > >> > Hi all, > >> > > >> > > >> > We've just submitted our paper to ICLR. We made the draft available > >> > at http://www.cs.toronto.edu/~cmaddis/pubs/deepgo.pdf > >> > > >> > > >> > > >> > I hope you enjoy our work. Comments and questions are welcome. > >> > > >> > > >> > Regards, > >> > Aja > >> > _______________________________________________ > >> > 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 > > > > > > > > _______________________________________________ > > 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 _______________________________________________ Computer-go mailing list Computer-go@computer-go.org http://computer-go.org/mailman/listinfo/computer-go
