There are some novel ideas in here worth appreciating. The classic “time scramble” is absolutely worth considering, even in top level human play.
It seems strange that even with fairly abundant datasets such as Lichess, that it is still difficult to approximate human strength with a bot.
As a “low strength human”, it’s very easy to see how traditional chess engines fail to emulate humans.
As far as actual calculation look ahead goes, humans aren’t calculating to chess engine depth. How often is a human really considering every possible move to greater than a 3 move depth?
Humans are moving with instinct. We cull the decision tree based on our evaluation of how promising a branch may be, not its objective calculated strength. This is where the chess engines break down.
Humans rely on instinct, pattern recognition, and strategy. None of this translates to a chess engine unless you are a top level player with near perfect instincts and pattern recognition.
My hunch is that for approximately human strength, the lowest ELO human makes moves completely at random, where the highest ELO human with follow the brute forced top lines. The challenge is tweaking the decision tree to match human evaluation of a branch based on skill level, and a second conditional probability of selecting a branch based on the player’s ELO.
The output of the chess engine shouldn’t be deterministic, but probabilistic. History has shown when you take a probabilistic approach to a problem, normally magic falls out. I’m yet to see a probabilistic chess engine.
It seems strange that even with fairly abundant datasets such as Lichess, that it is still difficult to approximate human strength with a bot.
As a “low strength human”, it’s very easy to see how traditional chess engines fail to emulate humans.
As far as actual calculation look ahead goes, humans aren’t calculating to chess engine depth. How often is a human really considering every possible move to greater than a 3 move depth?
Humans are moving with instinct. We cull the decision tree based on our evaluation of how promising a branch may be, not its objective calculated strength. This is where the chess engines break down.
Humans rely on instinct, pattern recognition, and strategy. None of this translates to a chess engine unless you are a top level player with near perfect instincts and pattern recognition.
My hunch is that for approximately human strength, the lowest ELO human makes moves completely at random, where the highest ELO human with follow the brute forced top lines. The challenge is tweaking the decision tree to match human evaluation of a branch based on skill level, and a second conditional probability of selecting a branch based on the player’s ELO.
The output of the chess engine shouldn’t be deterministic, but probabilistic. History has shown when you take a probabilistic approach to a problem, normally magic falls out. I’m yet to see a probabilistic chess engine.