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.{{Cite journal|url=https://philpapers.org/rec/GELIME|title=Information Measures, Effective Complexity, and Total Information|journal=Complexity|year=1996|volume=2|issue=1|pages=44–52|last1=Gell-Mann|first1=Murray|last2=Lloyd|first2=Seth|doi=10.1002/(SICI)1099-0526(199609/10)2:1<44::AID-CPLX10>3.0.CO;2-X|bibcode=1996Cmplx...2a..44G}}{{Cite journal |arxiv = 0810.5663|doi = 10.1109/TIT.2010.2053892|title = Effective Complexity and Its Relation to Logical Depth|journal = IEEE Transactions on Information Theory|volume = 56|issue = 9|pages = 4593–4607|year = 2010|last1 = Ay|first1 = Nihat|last2 = Muller|first2 = Markus|last3 = Szkola|first3 = Arleta|s2cid = 2217934}} 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 journal|url=https://philpapers.org/rec/MCAECA|doi=10.1086/375469|title=Effective Complexity as a Measure of Information Content|year=2003|last1=McAllister|first1=James W.|journal=Philosophy of Science|volume=70|issue=2|pages=302–307|s2cid=120267550}}