To make judgements more meaningful, first create (more) stable / quiet positions, then evaluate.Polama wrote:Where in your analysis did we consider that high 5 move? [...] every judgement in go is suspect.
With a quiet position, the follow-up variations space is "small".It's too large a state space.
A known method overrides unknown mind processes, which are inaccessible for everybody else.This is what your method, what no method, can substitute: the processing power of many minds over many years.
So what? Unless all those battles are recorded and analysed WRT to a particular joseki, they provide no or only little information, e.g., because other moves of the game can have greater impact on the "battles".So when we say joseki, we mean 'battle tested'.
No. For something to be a stronger claim / evidence, it must be described and it must be compared to the analysis.That's a stronger claim then any amount of analysis done over the course of a move in a game of go.
Where does this combined work consider even the basics of stone difference and influence properly? ALA even the combined work fails on explaining well the basics, it is by far not worth as much as you claim.the combined work of all the players exploring the consequences of joseki.
Not "of a player". The evaluation is essentially independent of the player doing it (if only it is done meaningfully according to the method).leichtloeslich wrote:he presents an "algorithm" which takes as input the positional judgement of a player and outputs a positional judgement.
No. It requires stone difference, territory count and influence stone difference. Application is easier for a quiet and stable position. Thickness is not required, but it can be one of the other, possibly significant aspects to be considered optionally.(Iirc his method requires evaluation of "thickness" and "stability"
1) My methods for whole board positional judgement.will RJ's method significantly improve upon the quality of the positional judgement?
2) My "joseki" evaluation method.
(1) is more generally applicable and more frequently relevant. So if you seek improvement in judgement, I suggest you start with it.
For (1) and (2), the quality of my positional judgements in my played, kibitzed or studied games / positions and strategic decision making due to them have improved greatly.
The method (2) does not take player judgements as input.the algorithm takes as input the judgements of a 3k