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All engines I'm aware of focus on finding the best moves to win the position. I'm curious whether there are any that exist that attempt to present an honest evaluation of a position, with human capabilities in mind. For example, with each candidate move, associate a weighted probability that indicates the likelihood a human is to actually find a given move on the board.

I'm thinking of situations where computers can find winning lines, but the key moves are so counterintuitive or unnatural that most humans would never consider them.

This is clearly a challenging computer science task. I'm also not even sure there's a good use case for such an engine. But, I'm curious.

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  • A good use case would be doing live commentary - doing commentary using stockfish or sesse is good if you want to compare people to computers, but if you're a human talking to other humans about what two humans are doing, you'll want an engine that thinks like a human. This is why such commentators tend to be high level players themselves - they are those engines that think like humans.
    – corsiKa
    Commented Dec 1, 2018 at 2:38
  • Related: chess.stackexchange.com/questions/13021/…
    – D M
    Commented Dec 1, 2018 at 2:45
  • The original poster says they're unsure of a good use for such a case, so I'd like to provide one: often, playing at the lower levels, I consider implementing an imperfect tactic. One that can be refuted, but the refuting move might not be obvious. I know the engine will ding me during analysis for starting the tactic, yet it might have succeeded or had a good chance at succeeding
    – Roy
    Commented Feb 11, 2023 at 19:01

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No engine do what you describe because it’s too hard to code a imperfect human brain. Estimating positional complexity at humans level is also quite hard.

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