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No, that's not necessarily how it works. Often (most?) of the time, heuristic solutions are also found by Complexity Theorists, and they usually can prove that
by edanm 8y ago
No, that's not necessarily how it works.
Often (most?) of the time, heuristic solutions are also found by Complexity Theorists, and they usually can prove that their solution is efficient for problems with certain characteristics, e.g. random data, not random data in a particular way, etc. These are then applied by the industry when they come across problems with these characteristics.
- deleted 8y ago[deleted]
- amelius 8y agoYes, that's simplifying the problem by making assumptions about the data. Except you often don't know what assumptions you can make. Better to check the assumptions using the data before devising an algorithm for the given type of data.
- edanm 8y agoI agree in principle. But imo in reality, what actually happens is: 1. Most data sets are roughly similar (or at least fall into one of a few cases). 2. Most algorithms are designed beforehand, on ideas of what data could be, not necessarily for actual data. Take for example sort algs. Sure, you could look at your data and devise a sort that exactly matches it most effectively. But in reality, in most cases, people just use quick sort, which is proven to be efficient on most data sets.