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Catch-Up: A game that stymies AI

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https://plus.maths.org/content/game-stymies-ai

INTRO: Artificial intelligence (AI) has succeeded spectacularly in certain kinds of tasks. These include playing specific games, such as Chess or Go, and finding patterns in images, such as identifying when a human organ is diseased or otherwise abnormal. It has done much less well in situations requiring more generalised learning, such as in understanding a text, or translating it from one language into another. Worse, acting like a human by expressing—and, especially, feeling—appropriate emotions seems well beyond AI's capacity.

AI is good at some specialised tasks, but not as good at more general ones.

AI's collection of tools, such as neural networks (find out more here), has helped to fuel recent advances, including the design of self-driving cars and trucks. Such advances require enormous computational power as well as smart algorithms to put this power to good use. With uncanny but not perfect accuracy, AI has been able to identify driving situations in which it is safe to proceed, slow down, speed up, turn, stop, or choose myriad variations on these basic actions, though not without incurring some fatal accidents.

It is surprising, therefore, to discover a game, Catch-Up, whose absurdly simple rules and a particular strategy have so far foiled AI's ability to outplay human players, whom it has trounced in much more complex games like Chess and Go. This is especially ironic when the human player makes random choices, which would be disastrous against an AI opponent in Chess or Go. I will suggest reasons why this is the case later, but first I describe the rules of Catch-Up and then consider what constitutes optimal play in it... (MORE - details)
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