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).