[saddestcatever]

If you haven't read Ender's Game, I highly recommend it based on this topic.

I think the tricky part is - if it's an unsolved problem, how does the game know when a task is complete? Feedback loops are a core element of game design, and part of the reason tedious tasks can be satisfying, but unless it's directly manual labor, I'm unsure how to create a proper feedback loop

[dumb1224]

I thought the same. Ender's Game and the cell classification task have something in common: the end status to achieve (whether to eliminate all opponents or identify something that's known). If we think this way, these two tasks could still be treated as machine learnable tasks (albeit poorer solution possibly). A genetic algorithm for example, could be trained to derive the means to achieve the goals. In cases where we don't know the end goal of the game, how do we train ourselves towards an unknown objective or without guidance of known answers.

[bee_rider]

Hmm.

Perhaps we could use bored humans as an accelerator to heuristically solve NP-complete problems. Then we'd just need to do the verification step.

All we need to do is prove that this produces a big-O improvement, and I think we could make a compelling business case.

/s