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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. 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.

See also

• Kolmogorov complexity
• Excess entropy
• Logical depth
• Renyi information
• Self-dissimilarity
• Forecasting complexity

References

1. Gell-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.
2. Ay, 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.
3. McAllister, James W. (2003). "Effective Complexity as a Measure of Information Content". Philosophy of Science. 70 (2): 302–307. doi:10.1086/375469. S2CID 120267550.

External links

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

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