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Even if the problem that markets are trying to solve is NP hard, this doesn't mean anything. Market forces are always subject to random factors. For practical purposes, randomized approximation algorithms are actually a great choice for tackling NP hard problems.


Sometimes. I think the simple answer to that is 'it depends on the problem'.


That's not an answer, that's an IOU for an answer, unless you can begin to describe broad classes of problems and how they differ.




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