Kolmogorov complexity: Difference between revisions

Revision as of 15:05, 12 October 2004

Revision as of 22:57, 15 October 2004

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information-theoretic. It has the desirable properties of statistical

invariance (the inference transforms with a re-parameterisation, such as from

polar co-ordinatescoordinates to Cartesian co-ordinatescoordinates), statistical consistency (even

for very hard problems, MML will converge to any underlying model) and efficiency (the MML model will converge to any true underlying model about as quickly as is possible). C.S. Wallace and D.L. Dowe showed a formal connection between MML and algorithmic information theory (or Kolmogorov complexity) in 1999.