[Computer-go] Move evalution by expected value, as product of expected winrate and expected points?

Robert Jasiek jasiek at snafu.de
Tue Feb 23 03:54:22 PST 2016


On 23.02.2016 11:36, Michael Markefka wrote:
> whether one could train a DCNN for expected territory

First, some definition of territory must be chosen or stated. Second, 
you must decide if territory according to this definition can be 
determined by a neural net meaningfully at all. Third, if yes, do it.

Note that there are very different definitions of territory. The most 
suitable definition for positional judgement (see Positional Judgement 1 
- Territory) is sophisticated and requires a combination of expert rules 
(specifying for what to detemine, and how to read to determine it) and 
reading.

A weak definition could predict whether a particular intersections will 
be territory in the game end's scoring position. Such can be fast for MC 
or NN, and maybe such is good enough as a very rough approximation for 
programs. For humans, such is very bad because it neglects different 
degrees of safety of (potential) territory and the strategic concepts of 
sacrifice and exchange.

I have also suggested other definitions, but IMO they are less 
attractive for NN.

-- 
robert jasiek



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