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Effective complexity is a measure of complexity defined in a 1996 paper by Murray Gell-Mann and Seth Lloyd that attempts to measure the amount of non-random information in a system.cite-ref-1[1]cite-ref-2[2] It has been criticised as being dependent on the subjective decisions made as to which parts of the information in the system are to be discounted as random.cite-ref-3[3]

• See also

• References

• External links

• Kolmogorov complexity

• Excess entropy

• Logical depth

• Renyi information

• Self-dissimilarity

• Forecasting complexity

cite-note-11. ↑ citerefgell-mannlloyd1996Gell-Mann, Murray; Lloyd, Seth (1996). "Information Measures, Effective Complexity, and Total Information". Complexity. 2 (1): 44–52. Bibcode:1996Cmplx...2a..44G. doi:10.1002/(SICI)1099-0526(199609/10)2:1<44::AID-CPLX10>3.0.CO;2-X.

cite-note-22. ↑ citerefaymullerszkola2010Ay, Nihat; Muller, Markus; Szkola, Arleta (2010). "Effective Complexity and Its Relation to Logical Depth". IEEE Transactions on Information Theory. 56 (9): 4593–4607. arXiv:0810.5663. doi:10.1109/TIT.2010.2053892. S2CID 2217934.

cite-note-33. ↑ citerefmcallister2003McAllister, James W. (2003). "Effective Complexity as a Measure of Information Content". Philosophy of Science. 70 (2): 302–307. doi:10.1086/375469. S2CID 120267550.

• http://www.cs.brandeis.edu/~pablo/complex.maker.html