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原文連結
論文資訊
- 類型：已發表論文
- 日期：2020-01-03
摘要
This work responds to a criticism of effective complexity made by James McAllister, according to which such a notion is not an appropriate measure for 資訊 content. Roughly, effective complexity is focused on the regularities of the data rather than on the whole data, as opposed to algorithmic complexity. McAllister’s argument shows that, because the set of relevant regularities for a given object is not unique, one cannot assign unique values of effective complexity to considered expressions and, therefore, that algorithmic complexity better serves as a measure of 資訊 than effective complexity. We accept that problem regarding uniqueness as McAllister presents it, but would not deny that if contexts could be defined appropriately, one could in principle find unique values of effective comple
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