Hi,

Is there a download link for the Michi --- Minimalistic Go MCTS Engine? I
would like to use it to learn how to build a Go engine ...

Gengyang

On Sat, Aug 22, 2015 at 8:00 PM, <computer-go-requ...@computer-go.org>
wrote:

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> Today's Topics:
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>    1. Re: Building A Computer Go AI (robertfinkng...@o2.co.uk)
>    2. Re: Building A Computer Go AI (Andy)
>    3. Re: Building A Computer Go AI (David Doshay)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Fri, 21 Aug 2015 13:06:16 +0100
> From: "robertfinkng...@o2.co.uk" <robertfinkng...@o2.co.uk>
> To: computer-go@computer-go.org
> Subject: Re: [Computer-go] Building A Computer Go AI
> Message-ID: <55d71438.2080...@o2.co.uk>
> Content-Type: text/plain; charset=utf-8; format=flowed
>
> Hi,
>
> Good news. There are a variety of open source projects out there,
> including both complete programs (Fuego, Pachi) as well as libraries to
> build your own Go engine (libEgo). There are also a wealth of papers
> explaining the theory behind the top algorithms. Try googling "AMAF
> algorithm" or "RAVE algorithm" or "MCTS algorithm" or "TD Search
> algorithm" as a starting point. There is a nice Thesis on Pachi too
> google "Pachi Thesis".
>
> I hope this helps :-)
>
> Regards
>
> Raffles
>
> On 21-Aug-15 8:48, CaiGengYang wrote:
> > Hello …
> >
> >
> > I am a 3d~~5d go player from Singapore.
> >
> > Keen to learn how to build a powerful Computer Go AI to compete in the
> Computer Go Tournament and also for admissions to a Computer Science
> college program.
> >
> > Have very little programming experience except following some code
> examples on CodeAcademy … how do I start building a Computer Go AI ?
> >
> >
> > Gengyang
> > _______________________________________________
> > Computer-go mailing list
> > Computer-go@computer-go.org
> > http://computer-go.org/mailman/listinfo/computer-go
> >
> > -----
> > No virus found in this message.
> > Checked by AVG - www.avg.com
> > Version: 2015.0.6125 / Virus Database: 4392/10476 - Release Date:
> 08/21/15
>
>
>
> ------------------------------
>
> Message: 2
> Date: Fri, 21 Aug 2015 09:22:45 -0500
> From: Andy <andy.olsen...@gmail.com>
> To: r...@ffles.com, computer-go <computer-go@computer-go.org>
> Subject: Re: [Computer-go] Building A Computer Go AI
> Message-ID:
>         <
> caatbd5dfpxmsnbhqh1v4m7s5-l0xzreud_kunr8i+wlzyek...@mail.gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> Here is a simple working implementation.
> https://github.com/pasky/michi
>
> >From the beginning of the readme:
>
> Michi --- Minimalistic Go MCTS Engine
>
> Michi aims to be a minimalistic but full-fledged Computer Go program based
> on state-of-art methods (Monte Carlo Tree Search) and written in Python.
> Our goal is to make it easier for new people to enter the domain of
> Computer Go, peek under the hood of a "real" playing engine and be able to
> learn by hassle-free experiments - with the algorithms, add heuristics,
> etc.
>
> The algorithm code size is 540 lines of code (without user interface,
> tables and empty lines / comments). Currently, it can often win against
> GNUGo on 9×9 on an old i3 notebook, be about even with GNUGo on 15×15 on a
> modern higher end computer and about two stones weaker on 19×19 (spending
> no more than 30s per move).
>
> This is not meant to be a competitive engine; simplicity and clear code is
> preferred over optimization (after all, it's in Python!). But compared to
> other minimalistic engines, this one should be able to beat beginner
> intermediate human players, and I believe that a *fast* implementation of
> exactly the same heuristics would be around 4k KGS or even better.
>
> Michi is distributed under the MIT licence. Now go forth, hack and peruse!
>
>
>
>
>
> On Fri, Aug 21, 2015 at 7:06 AM, robertfinkng...@o2.co.uk <
> robertfinkng...@o2.co.uk> wrote:
>
> > Hi,
> >
> > Good news. There are a variety of open source projects out there,
> > including both complete programs (Fuego, Pachi) as well as libraries to
> > build your own Go engine (libEgo). There are also a wealth of papers
> > explaining the theory behind the top algorithms. Try googling "AMAF
> > algorithm" or "RAVE algorithm" or "MCTS algorithm" or "TD Search
> algorithm"
> > as a starting point. There is a nice Thesis on Pachi too google "Pachi
> > Thesis".
> >
> > I hope this helps :-)
> >
> > Regards
> >
> > Raffles
> >
> >
> > On 21-Aug-15 8:48, CaiGengYang wrote:
> >
> >> Hello …
> >>
> >>
> >> I am a 3d~~5d go player from Singapore.
> >>
> >> Keen to learn how to build a powerful Computer Go AI to compete in the
> >> Computer Go Tournament and also for admissions to a Computer Science
> >> college program.
> >>
> >> Have very little programming experience except following some code
> >> examples on CodeAcademy … how do I start building a Computer Go AI ?
> >>
> >>
> >> Gengyang
> >> _______________________________________________
> >> Computer-go mailing list
> >> Computer-go@computer-go.org
> >> http://computer-go.org/mailman/listinfo/computer-go
> >>
> >> -----
> >> No virus found in this message.
> >> Checked by AVG - www.avg.com
> >> Version: 2015.0.6125 / Virus Database: 4392/10476 - Release Date:
> 08/21/15
> >>
> >
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> ------------------------------
>
> Message: 3
> Date: Fri, 21 Aug 2015 10:25:35 -0700
> From: David Doshay <ddos...@mac.com>
> To: computer-go@computer-go.org
> Subject: Re: [Computer-go] Building A Computer Go AI
> Message-ID: <0fc33771-37f2-4ea9-8a56-89a7a5d23...@mac.com>
> Content-Type: text/plain; charset=utf-8
>
> It depends very much upon what you mean by a “powerful Computer AI.” If
> you mean a modern Go playing program then all the advice about MCTS is
> good. If you mean an AI that depends more upon traditional Go knowledge,
> then the MCTS systems will not interest you, even though the mature MCTS
> bots are now much stronger than the traditional systems. If you are
> interested in the knowledge/pattern based systems then take a look at GNU
> Go. It is large and there will be a learning curve, but it is where I
> started when I built SlugGo, which was strong enough to win the KGS
> tournaments it entered until it was surpassed by the MCTS programs.
>
> Given your limited programming experience, I suggest Michi because Python
> is easy to read. While Libego is very fast, some of the C++ constructs can
> take a while to figure out, so modifying or adding to the code is harder.
>
> Good luck!
>
>
> Cheers,
> David G Doshay
>
> ddos...@mac.com
>
>
>
>
>
> > On 21, Aug 2015, at 12:48 AM, CaiGengYang <gengyang...@gmail.com> wrote:
> >
> > Hello …
> >
> >
> > I am a 3d~~5d go player from Singapore.
> >
> > Keen to learn how to build a powerful Computer Go AI to compete in the
> Computer Go Tournament and also for admissions to a Computer Science
> college program.
> >
> > Have very little programming experience except following some code
> examples on CodeAcademy … how do I start building a Computer Go AI ?
> >
> >
> > Gengyang
> > _______________________________________________
> > Computer-go mailing list
> > Computer-go@computer-go.org
> > http://computer-go.org/mailman/listinfo/computer-go
>
>
>
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> End of Computer-go Digest, Vol 67, Issue 14
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