Abstract
Chapter 4 brings together the insights of the first three chapters, and argues that the best way to understand ideal laws is to think of them as rules or algorithms for compressing empirical data. Idealization is explained as a form of lossy compression. Lossy compression is tolerated in scientific theories because of predictive redundancy in our theories. Idealizations in scientific theories and their application are accounted for as compression artefacts left over from the lossy compression. A number of possible objections to this explanation are considered and responses given.
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Wheeler, B. (2018). The Algorithmic Theory of Laws. In: Idealization and the Laws of Nature. SpringerBriefs in Philosophy. Springer, Cham. https://doi.org/10.1007/978-3-319-99564-9_4
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