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Part of the book series: Studies in Computational Intelligence ((SCI,volume 835))

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Abstract

The approximate range computation problem is one of the basic problem of interval computations. It is well known that this problem and even some special cases of it are at least as hard as any \(\mathbf {NP}\)-problem. First, we show that the general approximate range computation problem is not harder than \(\mathbf {NP}\)-problems. Then we show that the computional complexity of some further variants of this problem is closely related to some well-known open questions from structural complexity theory that seem to be slightly weaker than the famous open question whether the complexity class \(\mathbf {NP}\) is equal to the complexity class \(\mathbf {P}\), namely to the question whether \(\mathbf {NE}\) is equal to \(\mathbf {E}\), to the question whether \(\mathbf {NEXP}\) is equal to \(\mathbf {EXP}\) and, finally, to the question whether every \(\mathbf {NP}\)-real number is polynomial time computable.

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Acknowledgements

This article is dedicated to Professor Vladik Kreinovich on the occasion of his 65th birthday.

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Correspondence to Peter Hertling .

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Hertling, P. (2020). On the Computational Complexity of the Range Computation Problem. In: Kosheleva, O., Shary, S., Xiang, G., Zapatrin, R. (eds) Beyond Traditional Probabilistic Data Processing Techniques: Interval, Fuzzy etc. Methods and Their Applications. Studies in Computational Intelligence, vol 835. Springer, Cham. https://doi.org/10.1007/978-3-030-31041-7_15

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