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Deterministic Chaos and Computational Complexity: The Case of Methodological Complexity Reductions

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Abstract

Some problems rarely discussed in traditional philosophy of science are mentioned: The empirical sciences using mathematico-quantitative theoretical models are frequently confronted with several types of computational problems posing primarily methodological limitations on explanatory and prognostic matters. Such limitations may arise from the appearances of deterministic chaos and (too) high computational complexity in general. In many cases, however, scientists circumvent such limitations by utilizing reductional approximations or complexity reductions for intractable problem formulations, thus constructing new models which are computationally tractable. Such activities are compared with reduction types (more) established in philosophy of science.

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  1. Theodor Leiber
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Leiber, T. Deterministic Chaos and Computational Complexity: The Case of Methodological Complexity Reductions. Journal for General Philosophy of Science 30, 139–141 (1999). https://doi.org/10.1023/A:1008209231777

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