Effective complexity explained

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.^{[1] [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.^[3]

See also

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

External links

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

Notes and References

1. Information Measures, Effective Complexity, and Total Information. Complexity. 1996. 2. 1. 44–52. Gell-Mann. Murray. Lloyd. Seth. 10.1002/(SICI)1099-0526(199609/10)2:1<44::AID-CPLX10>3.0.CO;2-X. 1996Cmplx...2a..44G.
2. 0810.5663. 10.1109/TIT.2010.2053892. Effective Complexity and Its Relation to Logical Depth. IEEE Transactions on Information Theory. 56. 9. 4593–4607. 2010. Ay. Nihat. Muller. Markus. Szkola. Arleta. 2217934.
3. Effective Complexity as a Measure of Information Content. 10.1086/375469. 2003. McAllister. James W.. Philosophy of Science. 70. 2. 302–307. 120267550.