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By analogy with terms like NP-complete.


English Wikipedia has an article on:

AI-complete (not comparable)

  1. (artificial intelligence, informal) Of a problem: such that a solution presupposes or entails solving the problem of constructing a general artificial intelligence ("strong AI").
    • 2006, M.Gori, M.Ernandes, G.Angelini, “Cracking Crosswords: The Computer Challenge”, in Oliviero Stock, Marco Schaerf, editors, Reasoning, Action and Interaction in AI Theories and Systems: Essays Dedicated to Luigia Carlucci Aiello, Springer Science & Business Media, →ISBN, page 266:
      Problems like solving crosswords from clues are reputed as AI-complete [7]. This enormous complexity is due to its semantics and the large amount of encyclopaedic knowledge required.
    • 2007, Ben Goertzel, Cassio Pennachin, Artificial General Intelligence, Springer Science & Business Media, →ISBN, page 452:
      Just as concept kernels are not AI-complete, sequiturs and resonances are not AI-complete. Sequiturs and resonances also may not need to be human- equivalent to minimally support deliberation; it is acceptable for an early AI to miss out on many humanly obvious thoughts, so long as those thoughts which are successfully generated sum to fully general deliberation.
    • 2014, Nick Bostrom, Superintelligence: Paths, Dangers, Strategies, Oxford University Press, →ISBN, page 71:
      ... Now imagine a remote descendant of such a system that has acquired the ability to read with as much understanding as a human ten-year-old but with a reading speed similar to that of TextRunner. (This is probably an AI-complete problem.)


Further reading[edit]