[computer-go] Re: computer-go Digest, Vol 34, Issue 15

[Rémi Coulom]

David Silver wrote:
> Very interesting paper!
>
> I have one question. The assumption in your paper is that increasing 
> the performance of the simulation player will increase the performance 
> of Monte-Carlo methods that use that simulation player. However, we 
> found in MoGo that this is not necessarily the case! Do you think 
> there is some property of your learning algorithm that makes it 
> particularly suitable for Monte-Carlo methods?
>
> Thanks!
> Dave 
Maximizing the likelihood does not optimize the performance of the 
simulation player. For instance, by making it more greedy, I am sure it 
would become a stronger player. I have the feeling that maximizing the 
likelihood produces a good balance between playing good moves and being 
random. It would be worth testing the strength of the MC player with 
more or less greedy versions of the random player to test this.

Rémi