Pio wrote: ↑Sat Jul 04, 2020 9:58 pm

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Honestly I have always thought that it was strange that the win probability was not the standard. There is no problem using win probabilities in an alpha beta framework (just think opponent’s win probability = 1 - my win probability. Thinking in win probabilities is much more intuitive and can also help when tuning the evaluation, deciding on pruning thresholds... .

+1

You are absolutely correct. The first known attempt to evaluate the pieces was made by H. M. Taylor in 1876 [4], reported by Coxeter (1940, pp. 162-165 [5]). The value of a piece was taken as proportional to the average number of squares controlled, averaged over all 64 positions of the piece on the board. Later, in 1949, Claude Shannon in his 1949 paper "Programming a Computer for Playing Chess" also proposed the {1, 3, 3, 5, 9} point values for {pawn , knight, bishop, rook , queen}. I am not certain who first proposed those piece values, but I believe it was considered common knowledge prior to Shannon's book. Anyway , piece values were developed as a means not only to teach new players. but it was also used to develop the first chess programs. Now in 2020, we have machine learning models that do not even considered the piece values at but only considers win draw and loss probabilities based on millions and millions of game played at at very fast time controls. I happen to believe scoring probabilities is the more natural way to score an expected outcome of a game - any game frankly for a human. That is also one reason why betting is so popular

Centiapawn evaluations typically range from -100 to +100 centipawn, But the expected outcome for a loss is at 100% from -5 to minus -100 (roughly) and the expected outcome of a win is at 100% win from +5 to +100 (roughly) . How many times do we ( or did we ) pay attention to centipawn below -5 and above +5 - we do all the time! BUt the reality is that the game is already over. Our attention is perhaps better utilized focusing on games where the win or loss is below 100% if we want to learn something from the game. We have all this real estate ( 190 Centipawns) where the outcome is already a forgone conclusion - and we have this small windows of 10 centpawns ( minus 5 to plus 5) where it is not. I really think that is why many players will prefer centipawn - not that the information will give them some new profound insight - it is simply a much more natural filter to focus on what is important.

Prediction - a hundred years from now, centipawn evaluation output will be obsolete, People of the business today are very much wired to probabilities. In business today everything is risk evaluated as what can go right, what can wrong. Business decisions, investing, insurance decisions , government decisions, medical treatment decisions - they are all based on probability and risk - not on some contrived and abstract centipawn evaluation that is relatively loosely connected a win probability the desired outcome. It only came into being because there was nothing better. Now granted - Stockfish is still centipawn like scoring internally - and the highest rated CP move is still being played - all SF is doing is assigning that centipawn scoring to a percent winning score and the using some historical data that fits to a model based on millions of games to output WDL. The WDL is simply a model - and we all know how well models performed during the recent COVID-19 crisis- sometimes not very well. In some respects we do calculate the scoring percentage in our head anyway e.g., I'm two pawns up, I like my winning chances.

It's human nature for people to be resistant to change. I have seen it all my life. It is probably the single biggest reason why some very successful companies in their day are no longer here - they did not change or changed quick enough. That list is quite long.