TY - CHAP

T1 - Differences between Kolmogorov Complexity and Solomonoff Probability: Consequences for AGI

AU - Potapov, A.

AU - Svitenkov, A.

AU - Vinogradov, Y.

PY - 2012

Y1 - 2012

N2 - Kolmogorov complexity and algorithmic probability are compared in the context of the universal algorithmic intelligence. Accuracy of time series prediction based on single best model and on averaging over multiple models is estimated. Connection between inductive behavior and multi-model prediction is established. Uncertainty as a heuristic for reducing the number of used models without losses of universality is discussed. The conclusion is made that plurality of models is the essential feature of artificial general intelligence, and this feature should not be removed without necessity.

AB - Kolmogorov complexity and algorithmic probability are compared in the context of the universal algorithmic intelligence. Accuracy of time series prediction based on single best model and on averaging over multiple models is estimated. Connection between inductive behavior and multi-model prediction is established. Uncertainty as a heuristic for reducing the number of used models without losses of universality is discussed. The conclusion is made that plurality of models is the essential feature of artificial general intelligence, and this feature should not be removed without necessity.

M3 - Article in an anthology

SP - 252

EP - 261

BT - proceedings of AGI 2012, Lecture Notes in Artificial Intelligence

PB - Springer Nature

ER -