I still don't understand.SMIRF wrote: The moment when the decision is made to call quiescence(), then only (in major cases) material exchanges should be investigated and not quiet moves. For me it does not seem to make sense, to ignore possible fluctuations whithin possible quiet moves, but to take those from captures into the evaluation.
My idea is, to use the detail evaluation from the root of quiescence and use it approriately through the whole quiescence search +/- , because any more precision would be an illusion. Moreover it could change the possible outcome, when the alpha-beta window later would be modified and the same node would be evaluated a second time, and fluctuating sub node detail evaluations would lead to different cuts.
Assuming that you have a standard iterative deepening loop where the search is recursed until some depth D. Once you reach depth D you evaluate the leaf node and back up the score.
How do you evaluate it? Simply returning static eval is inaccurate if there is unresolved tension in the position, so you call the quiescence search function to resolve the tension. At each node in the quiescence search you call the static evaluation function, so I don't understand "use the detail evaluation from the root of quiescence and use it approriately through the whole quiescence search +/- , because any more precision would be an illusion". The static evaluation at the beginning of QS is likely inaccurate.
As for ignoring improvements due to possible quiet moves: that's not the point of QS, that's what the next iteration of iterative deepening is for. QS is to avoid returning a good score in a position where you hang a queen.
There is an argument to be made that some "quiet" moves are not truly "quiet" in that making them could cause a huge swing in score (king-safety is a likely candidate). If you have a reliable way to detect those, then you can certainly include them in QS, and it will be more accurate. Whether it's better depends on whether the increased cost of evaluating the node is offset by the improved accuracy of QS, bearing in mind that iterative deepening will find such moves eventually anyway.