Thanks for the replies to my first message; i looked at the links you
supplied and comment on them later in this email.
I noticed that Google does not show you the playlist when you look at
episode 1 of the series (of currently 3 videos), so you may have missed the
second two episodes which are more significant than the first. Here is a
link to the playlist:
https://www.youtube.com/playlist?list=PL4y5WtsvtduqNW0AKlSsOdea3Hl1X_v-S
episode 2 introduces mental images and episode 3 is a conversation between
Hajin Lee and me about her thoughts on a couple of moves early in one of
her games. It includes my first attempt at picturing her thoughts, both
as symbolic information structures and as paint overlays on the game board.
My hope is that the former might one day become the basis of symbolic
generic heuristic rules that could be used to generate and evaluate move
candidates and the latter could evolve into useful instructional materials
for people learning the game - so that they can, so to speak, look through
the eyes of an expert like Hajin.
To these ends, i need the assistance of people with better skills than me
at (a) drawing pictures, (b) software and (c) Go. I think that programming
is like gymnastics - best done by the young, with their abundance of
enthusiasm and energy. I enjoyed programming 50 years ago, but i'm too old
in the tooth now to burn midnight oil.
Now to your replies:
Folkert: Stop is a good start but as you already know, there's a long way
to go yet :)
Steven: I expect there is a future for CNN's in recognising static images,
but my gut feel is that a position in a Go game is more like one frame of a
movie; as such, it requires a technology that can interpret dynamic images
- maybe work being done in automatous car driving can contribute something
useful to Go playing? Nevertheless, I was surprised by the many humanlike
moves of DCNNigo on KGS (until it revealed its brittleness). To be sure,
drawing upon the moves of experts is one way of gaining expertise, but my
feeling is that one should try to abstract the position - to generalise
from the examples - so that general knowledge can be formed and applied to
novel situations. It may be that a CNN arguably does do some kind of
generalisation - but can it, for example, characterise something as basic
as the waist of a keima?
Ingo: Tanja may be the kind of artist who could produce nice drawings of
Hajin's mental images, perhaps based on my own crude sketches? It would be
unpaid work though... I liked Fuego's and Jonathan's territory pictures,
which reminded me of Zobrist's early work on computing influence. [Albert
Zobrist (*1969*). *A Model of Visual Organisation for the Game of Go*.
Proceedings of the Spring Joint Computer Conference, Vol. 34, pp. 103-112.]
However, whereas being able to picture influence and territory is one of my
objectives, i want to try to picture the richness of what Hajin (aka
Haylee) sees rather than the result of a primitive computation. For
example, at 10:24 in episode 3, she points out that when black is on J4
instead of K4, there is an opening in black's lower side for white to
invade. This tiny gap makes all the difference to the dynamic meaning of
the position a few moves prior (ie whether it is sensible for white to
approach Q3 at Q5).
One of the major influences on my own thinking about Go programming is the
seminal work Thought and Choice in Chess by Adriaan de Groot which i
reckon is well worth a read by anyone interested in programming Go
https://books.google.com.au/books?id=b2G1CRfNqFYCpg=PA99
---
personal website http://sites.google.com/site/djhbrown2/home
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