Yes, it was in Andy Olsen's original response: https://github.com/pasky/michi
Dave
Origineel Bericht
Van : gengyang...@gmail.com
Datum : 24/08/2015 10:24
Aan : computer-go@computer-go.org
Onderwerp : Re: [Computer-go] Computer-go Digest, Vol 67, Issue 14
Hi,
Is there a download link for the
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 ar
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
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
Check out http://senseis.xmp.net/?UCT
this is a basic Monte Carlo bot, probably 25k in strength
the way it works is better explained here:
https://en.wikipedia.org/wiki/Monte_Carlo_tree_search
but I didn't understand the article until I looked at the Sensei's
library implementation first
On 2
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
CodeAcad
