Effective complexity
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]
References
- https://philpapers.org/rec/GELIME
- 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.
- https://philpapers.org/rec/MCAECA
See also
- Kolmogorov complexity
- Excess entropy
- Logical depth
- Renyi information
- Self-dissimilarity
- Forecasting complexity
External links
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