RE: [computer-go] Addressing the root of the problem

[Anton Safonov <anton.safonov@xxxxxxx>]

> From:
> "Daniel Burgos" <Daniel_Burgos@xxxxxxxxxxxxxxxxx>
> Date:
> Thu, 7 Oct 2004 13:53:17 +0200
> To:
> "computer-go" <computer-go@xxxxxxxxxxxxxxxxx>
>
>
>
> I'm following that approach to solve Go: find a small set of
> rules/patterns (as small as possible) to evaluate a board in order to
> decide where is worth to play. I want to cut down the decision tree.
>
> I think my hypothesis is the same as yours: because the complexity of go
> is coming from its small set of rules (but very well designed), its
> solution should be something similar.
>
> Something inspired in the small rules that allow creating complex
> figures as the fractals.
>  
I guess, it could be some mix of cellular automata and neural networks...

> But, what is this set of rules? This is the winning answer, if our
> hypothesis are correct I'm afraid...
>
> I'm implementing evolution algorithms for that, but they are only in
> design stage by now.
>  
I tried to establish some rules which will grow the needed "fractal", 
but suddenly came to the conclusion, that all my constructions repesent 
a less powerfull system.
Now trying to design a meta-system with even less rules (one could be 
tracking that produced end-system must be "at the edge of chaos"), which 
is given a set of building blocks (for rules) and evolves the rules, 
which in turn will grow the end-system.
I.e. "meta-system" --(evolution)->  "rules" --(grow)-> "solution system"

Anton.


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