Machine learning models have already mastered Chess, Go, Atari games and more, but in order for it to ascend to the next level, researchers at Facebo

Decades-old ASCII adventure NetHack may hint at the future of AI

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2021-06-09 21:30:05

Machine learning models have already mastered Chess, Go, Atari games and more, but in order for it to ascend to the next level, researchers at Facebook intend for AI to take on a different kind of game: the notoriously difficult and infinitely complex NetHack.

“We wanted to construct what we think is the most accessible ‘grand challenge’ with this game. It won’t solve AI, but it will unlock pathways towards better AI,” said Facebook AI Research’s Edward Grefenstette. “Games are a good domain to find our assumptions about what makes machines intelligent and break them.”

You may not be familiar with NetHack, but it’s one of the most influential games of all time. You’re an adventurer in a fantasy world, delving through the increasingly dangerous depths of a dungeon that’s different every time. You must battle monsters, navigate traps and other hazards, and meanwhile stay on good terms with your god. It’s the first “roguelike” (after Rogue, its immediate and much simpler predecessor) and arguably still the best — almost certainly the hardest.

Its simple ASCII graphics, using a g for a goblin, an @ for the player, lines and dots for the level’s architecture, and so on, belie its incredible complexity. Because Nethack, which made its debut in 1987, has been under active development ever since, with its shifting team of developers expanding its roster of objects and creatures, rules, and the countless, countless interactions between them all.

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