[computer-go] Hybrid theory

[David Doshay]

Yes, I would like to see the references. I also wonder how similar
the statistical estimators are to each other. Do they represent
data and estimates in the same way?

We are trying to move towards a design that mixes intrinsically
different kinds of engines. Neural Networks, UCT/MC, Gnu Go,
tile/pattern matching systems, etc., can all have very different
ways of representing why a particular choice is the highest
valued and what the distance is between the lower valued choices.

Cheers,
David



On 1, Feb 2008, at 12:29 PM, Alain Baeckeroot wrote:

> Le vendredi 1 février 2008, David Doshay a écrit :
>> This is the direction in which we are moving with SlugGo. We also
>> expect it to be difficult to integrate different approaches, but this
>> has always been our research direction: when there are multiple
>> codes which will each give an evaluation of a situation, how does
>> one design an arbitrator that makes the final decision?
>>
> There is a phD student in my lab working on such a topic in speech
> recognition (use several different statistical estimators and combine
> the informations to get the "best one" or the "best tree").
> This give some nice improvements:
> more or less 5 engines with 25 % error, give a system which does  
> 20% error,
> and this is a huge improvement.
>
> I'll post some references, i guess the tools and methods are more  
> or less
> well known.
>
> Alain
>
>
>
> _______________________________________________
> computer-go mailing list
> computer-go at computer-go.org
> http://www.computer-go.org/mailman/listinfo/computer-go/