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Comment by elijaht | Hacker News Reader

The article mentions that “It simply doesn't have data about full moon variables in its training data, so a branching series of decisions likely leads to lesser outcomes, or just confusion.”

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It does say that, but I'd like to know more about the mechanisms involved. The problem is that every action you take generates better results than you'd expect. I can see why prediction would be worse while that's going on, but why would performance be reduced?

I can imagine it's a bit like if gravity suddenly changed to 0.9g. Everything(?) is easier but a lot of people would probably stumble around a bit before muscle memory, coordination etc. get used to the change.

I believe games like NetHack have monkey paw situations where fortune may not actually be that fortunate

My memory has not lasted well

Nethack is weird. It's literally a game comprised of a huge number of special cases all welded together. A lot of the crucial info for playing the game is not really discoverable through the interface, so Humans used to mostly learn the game by reading the source code and now they mostly learn the game by reading guides.

The bug here is not in nethack but just in the training, which meant some of the special cases (full moons, fri 13ths etc) weren't in the training data. They should have been running the training in VMs with the clock set to include these cases.

Honestly a lot of the reporting of this "bug" seems wildly overblown.

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