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Thanks for your comment. I don't see how the difficulty of a problem alters the class of the algorithm that is applied towards finding a solution; the algorithm

Thanks for your comment. I don't see how the difficulty of a problem alters the class of the algorithm that is applied towards finding a solution; the algorithms that we used here are mentioned in almost every classic textbook on AI (Russel, Norvig etc.). If you're alluding towards the difference b/w weak and strong AI, then that's another discussion (btw, I didn't down-vote your comment).

gjm11 13y ago
(Sorry for the slow reply.) Yes, these optimization algorithms are used in AI. But that doesn't make them AI. Loops are used in AI; strings are used in AI; but a loop isn't an "AI algorithm" and a string isn't an "AI data structure", and writing a program that uses strings and loops wouldn't be "using AI to [do whatever]". Simulated annealing is a less trivial thing than loops and strings. But it still isn't specifically an AI technique. Simple hill-climbing optimization, even less so. I'm pretty sure that a hefty majority of the uses of these things is unambiguously not AI unless AI is defined super-broadly (e.g., as "doing something tricky with a computer"). (No, I wasn't alluding to the distinction between "weak" and "strong" AI. I'm perfectly happy to call things AI that don't come close to actually implementing human-like intelligence!)