Abstract
Generalizing several results from complex analysis, A. Bloch formulated an informal principle—that for every global implication there is a stronger local implication. This principle has been formalized for complex analysis, but is has been successfully used in other areas as well. In this paper, we propose a new formalization of Bloch’s Principle, and we show that in general, the corresponding localized version can be obtained algorithmically.
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Acknowledgements
This work was supported in part by the National Science Foundation grants HRD-0734825, HRD-124212, and DUE-0926721.
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Ceberio, M., Kosheleva, O., Kreinovich, V. (2018). From Global to Local Constraints: A Constructive Version of Bloch’s Principle. In: Ceberio, M., Kreinovich, V. (eds) Constraint Programming and Decision Making: Theory and Applications. Studies in Systems, Decision and Control, vol 100. Springer, Cham. https://doi.org/10.1007/978-3-319-61753-4_4
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DOI: https://doi.org/10.1007/978-3-319-61753-4_4
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