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Kosh
PageType: HomePage     Keywords: Software

Jack Ha,

Kosh 4k on KGS

I'm a 24 year old student of computer science. My final assignment is about computer go, so all comments or ideas are welcome. I'm interested in search trees and learning algorithms for local situations. The goal is to find a solution with no hand coded knowledge, as fast as possible (= minimum iterations).

Everything is done in [ext] Python, a quite flexible high level programming language.

This page hasn't been updated for a long time, but so far I have successfully implemented:

  • Lambda search using proof number search
  • Proof number move generator, which converts candidate moves into childmoves or refutes them and uses the Relevancy Zone output of a Lambda search for child candidates.
  • Several heuristics, including history heuristic as well as a Learning Shape heuristic. The latter uses common fate graph like features at different detail levels.
  • A hashing function for repeating board situations
  • Simple multigoals (e.g. Capture string A or Capture string B)
  • A very bad playing program. It uses bouzy's 21/5, tactical heuristics and the tactical search.

What it can do:

  • Solve different tesuji problems: knights move, loose ladder, slapping tesuji, clamping tesuji, nose tesuji, snapback, throw-in, ladder building. (Not yet: crosscut tesuji, a placement tesuji problem)
  • Solve simple life/death problems
  • Learn from experience and solve similar problems faster
  • Play go very bad

Still planning to do:

  • Make a reasonable playing program using the tactical search (and other 'tools').
  • Optimize different parts

Does anybody have a good method to make a reasonable playing program at all? I like to hear it!

Feel free to add text to this page.


[Diagram]

searching capture (3, 3), (9, 3) (= capture A or B)

Solves in 540 iterations/5 seconds on my 1 Ghz P3


[Diagram]
sequence


[Diagram]

Solves in 40.000 iterations/450 seconds


[Diagram]
sequence


This is a copy of the living page "Kosh" at Sensei's Library.
(OC) 2004 the Authors, published under the OpenContent License V1.0.