Re: computer-go: Neural network minimax hybrid paper

["Ran Xiao" <ranxiao@xxxxxxxxxxxx>]

Julian,

The key issue is not whether we can implement NN or not in GO, but what we
let an NN to learn, or what we knew the measure that is about right to make
a decision.

I think looking at 5x5 grid to decide a move will happen in 6 steps thus
assign a value from 1 down to 0 is too simple. How will this mechanism to
deal with opening with most area open or during the fights most 5x5 grid
looks similar? Picking another 6 unlikely moves to balancing 6 likely moves
does not sounds right because the 0-value case already is an unlikely move.

I think 5x5 grid can at most learn some local reaction, not even influence.
I do not know how do you deal with corners and edges. If the potential move
is still centered, the effective area is even small.

The small 25x10x1 NN can remember about 250 patterns with symmetrical moves
removed. Is not it too few for a 5x5 board area?

Weimin

----- Original Message -----
From: "Julian Churchill" <jjc97c@xxxxxxxxxxxxxxxxx>
To: <computer-go@xxxxxxxxxxxxxxxxx>
Sent: Sunday, December 02, 2001 5:52 AM
Subject: computer-go: Neural network minimax hybrid paper


>
> Hi,
>
>  I just came back from presenting my paper at a conference and it seemed
to
> go down quite well, so I wondered if anyone here might be interested in
> having a look. The title is "A new computational approach to Go", which
> doesn't really give away much, so here is the abstract: