I wonder if one can find empirical evidence of a link between the Kolmogorov complexity of a task and that of its solutions. Intuitively, I would think that problems that are simple to fully specify can be solved with comparably simple algorithms.
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There are many problems that are easy to state but provably impossible to solve such as the halting problem and satisfiability of first order logic. How would that affect your hypothesis?
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We're talking about solvable tasks, and concerned not about runtime complexity but instead about Kolmogorov complexity of the shortest possible solution
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Anecdotal, not empirical, but: Collatz conjecture (easy to state, unsolved), and "return the last digit of this huge, incompressible number" (big KC, trivial)
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But this is a joke account tralala don't mind me!
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I question the value of KC descriptive complexity as a tool for assessing problems and/or getting to general AI! Most supply chain AI problems I work on are simple to "describe" but implmntn vary widely. As you know, in DL, 25lines of code can have huge variation in complexity
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I agree with this sentiment. I doubt there's a relationship with algorithmic complexity and general intelligence. Human's have general intelligence but are no where near the capabilities of computers in performing algorithms.
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