The speed prior is a complexity measure similar to Kolmogorov complexity, except that it is based on computation speed as well as program length.[1] The speed prior complexity of a program is its size in bits plus the logarithm of the maximum time we are willing to run it to get a prediction.

When compared to traditional measures, use of the Speed Prior has the disadvantage of leading to less optimal predictions, and the advantage of providing computable predictions.

See also

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References

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  1. ^ Schmidhuber, J. (2002) The Speed Prior: A New Simplicity Measure Yielding Near-Optimal Computable Predictions. In J. Kivinen and R. H. Sloan, editors, Proceedings of the 15th Annual Conference on Computational Learning Theory (COLT 2002). Lecture Notes in Artificial Intelligence, pages 216--228. Springer.[1]
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