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→Algorithmic information models： 翻译1
===Algorithmic information models===
===Algorithmic information models算法信息模型===
Compare two programs, both of which output both X and Y.
Compare two programs, both of which output both X and Y.
比较两个同时输出 x 和 y 的程序。
比较两个同时输出 X 和 Y 的程序。
* Store Y and a compressed form of X in terms of uncompressed Y.
* Store Y and a compressed form of X in terms of uncompressed Y.
* Store X and a compressed form of Y in terms of uncompressed X.
* Store X and a compressed form of Y in terms of uncompressed X.
* 用未压缩的 X 来存储 X 和压缩形式的 Y 。
The shortest such program implies the uncompressed stored variable more-likely causes the computed variable.<ref>Kailash Budhathoki and Jilles Vreeken "[http://eda.mmci.uni-saarland.de/pubs/2016/origo-budhathoki,vreeken.pdf Causal Inference by Compression]" 2016 IEEE 16th International Conference on Data Mining (ICDM)</ref><ref>{{Cite journal |doi = 10.1007/s10115-018-1286-7|title = Telling cause from effect by local and global regression|journal = Knowledge and Information Systems|year = 2018|last1 = Marx|first1 = Alexander|last2 = Vreeken|first2 = Jilles|volume=60|issue = 3|pages=1277–1305|doi-access = free}}</ref>
The shortest such program implies the uncompressed stored variable more-likely causes the computed variable.<ref>Kailash Budhathoki and Jilles Vreeken "[http://eda.mmci.uni-saarland.de/pubs/2016/origo-budhathoki,vreeken.pdf Causal Inference by Compression]" 2016 IEEE 16th International Conference on Data Mining (ICDM)</ref><ref>{{Cite journal |doi = 10.1007/s10115-018-1286-7|title = Telling cause from effect by local and global regression|journal = Knowledge and Information Systems|year = 2018|last1 = Marx|first1 = Alexander|last2 = Vreeken|first2 = Jilles|volume=60|issue = 3|pages=1277–1305|doi-access = free}}</ref>
最短的这种程序意味着，更有可能是未压缩的'''<font color='#32cd32>存储变量stored variable</font>'''导致了'''<font color='#32cd32>计算出的变量computed variable</font>'''。
===Noise models===
===Noise models===