RE: [computer-go] Computer Go hardware

["David Fotland" <fotland@xxxxxxxxxxxxxxx>]

Your approach sounds reasonable.  There was a Japanese group that did a
program based on learning patterns by finding the significant parts due
and splitting to form new patterns and growing them.  Do you know of it?
Maybe around 1990?

Michael Reiss worked on extracting patterns for move selection
automatically,
and got pretty good pro prediction.  I think later he abandoned it for
patterns
that were selected by a very strong player instead.  Michael, can you
comment?

David

> -----Original Message-----
> From: computer-go-bounces@xxxxxxxxxxxxxxxxx 
> [mailto:computer-go-bounces@xxxxxxxxxxxxxxxxx] On Behalf Of 
> Frank de Groot
> Sent: Wednesday, October 20, 2004 1:55 AM
> To: computer-go
> Subject: Re: [computer-go] Computer Go hardware
> 
> 
> 
> From: "David Fotland" <fotland@xxxxxxxxxxxxxxxxx>
> 
> >I don't know anyone that's worked full time on computer go
> >for very long.
> 
> Well I did but due to chronic illness I spent not much more 
> actual time on it than you did, per week. I sit behind the PC 
> but nothing comes out of my hands because instead of 
> concentrating I get paranoid rages :) I would say I spent 
> about 0.5 actual year. About half of that was GUI-work, like 
> making toolbars dock better :)
> 
> I started a contract job on my birthday two days ago after 
> having been at Go for the past 2 years but I quit after one 
> day. Embedded C/Assembly and linux on a terminal can be OK 
> but not when you're close to something marketable.. It's not 
> that I can't use the money..
> 
> 
> > Tuning the heuristics by hand is pretty tedious.
> 
> I try to avoid that.
> It took me 2 years to figure out a way that will really help 
> a lot in the next stage. I reached about 15% pro-prediction 
> with my current pattern system.
> 
> I want to bring that to 20% or a bit more.
> So I will use the pattern system as one input of a NN, but a 
> lot more stuff will go in. Stuff that my pattern system has 
> no grasp of. So when the NN is designed well and when it gets 
> the proper training, it should significantly outperform the 
> pattern system.
> 
> So my job is to say: "There is such a thing as patterns, 
> pattern have a min/max nr. of stones in them, patterns have 
> sizes, patterns have values" etc. and the pattern system 
> learns them by itself and adjust their values too.
> 
> Same with the NN of course but I will use that only to 
> augment the pattern system at the moment and will not yet 
> improve the fact that it is near-blind to tactical situations.
> 
> I'm about to start the NN experiments in a few days.
> They look very promising, I did some preliminary work and 
> some good moves that were consistently rated very low by the 
> pattern system (due to its
> weaknesses) suddenly got into full focus by the NN.
> 
> 
> >I don't think it is possible to make a strong program by extracting
> millions
> >of patterns from professional games and sorting through them 
> >automatically.
> 
> Me neither.
> Neither will a strong program be produced by combining a 
> pattern system with a Neural Network, except when you manage 
> to extract tactical info. It would be nice but I agree that 
> search is unavoidable.
> 
> I think that 4 ingredients cooked the right way will do the trick:
> 
> - pattern system
> - neural network
> - search
> - genetic optimization of various parameters in and between 
> the pattern modules, search and NN.
> 
> All combinations may be neccessary, like using a part of the 
> pattern system in the first few ply of search etc.
> 
> But that is my plan.
> I will take search very seriously, meaning I will spend years 
> on it. I see it as the core of a Go program that has a shot 
> at becoming really good.
> 
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