On 20.12.2014 17:04, Erik van der Werf wrote:
the critical part is in learning about life &
death. Once you have that, estimating ownership is fairly easy
> [...] See the following papers for more details: [...]
http://erikvanderwerf.tengen.nl/pubdown/predicting_territory.pdf
Estimating ownership or evaluation functions to predict final scores of
already played games are other things than estimating potential
territory. Therefore I dislike the title of your paper. Apart from lots
of simplistic heuristics without relation to human understanding of
territorial positional judgement, one thing has become clear to me from
your paper:
There are two fundamentally different ways of assessing potential territory:
1) So far mainly human go: count territory, do not equate influence as
additional territory.
2) So far mainly computer go: count territory, equate influence as
additional territory.
Human players might think as follows: "The player leads by T points.
Therefore the opponent has to use his superior influence to make T more
new points than the player." Computers think like this: "One value is
simpler than two values, therefore I combine territory and influence in
just one number, the predicted score."
Both methods have their advantages and disadvantages, but it does not
mean that computers would always have to use (2); they can as well learn
to use (1). (1) has the advantage that counting territory (or
intersections that are almost territory) is "easy" for quiet positions.
Minor note on your paper: "influence" and "thickness" are defined now
(see Joseki 2 - Strategy) and "influence stone difference" and
"mobility" are related concepts if one wants simpler tools. "aji" has
approached a mathematical definition a bit but still some definition
work remains.
--
robert jasiek
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