3 ms·
I don't entirely disagree but consider the following: 1) To be useless to a top player, the decision tree needs to have only long term gains and be barren in t
by Bakary 4y ago
I don't entirely disagree but consider the following:
1) To be useless to a top player, the decision tree needs to have only long term gains and be barren in terms of short term human-readable profits.
2) In the same vein, the metagaming pruning process you have described has to unfold a certain way, in the context of a game where most of the previous moves have been played by humans and not machines and where there is therefore much more of a chance of an unbalance compared to a purely computed position.
3) the above criteria of long-term, short-term, readability etc. must be defined according to players that are already 95% or so precise. The missing percentages mean that they always get smoked by machines over the course of a game, but can have a remarkable ability to see good lines.
- treis 4y agoThe problem is if we're sending 1 bit of information that is something along the lines of "go for it" or "something's there" or whatever. That's just not something an engine can tell you outside of specific scenarios where there is a really good move to be made. You probably could rejigger the engine to factor into account the likelihood of a human finding the right moves and relative downside. Like an engine might reject a move that leaves them a half pawn down if the opponent makes 25 difficult to find moves in a row. But that risk/reward would be worth it going against a flawed human player. Perhaps it could also work in conjunction with another GM that you train with regularly. They can use an engine and do the evaluation above themselves.
- Bakary 4y agoI see what you mean. This would indeed be most useful with an accomplice, and a lot dicier and ambiguous without.