Alexey Potapov - Differences between Kolmogorov Complexity and Solomonoff Probability
1,366 views · Published 6 July 2013 · 59:04 · Indexed 14 November 2026
Channel: Science, Technology & the Future · 2013 · Science & Technology
Winter Intelligence Oxford - AGI12 - http://agi-conference.org/2012 ==Differences between Kolmogorov Complexity and Solomonoff Probability: Consequences for AGI== (this video includes discussion afterwards - though the video is blurred. Abstract. 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 multimodel 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. Key words: Universal Agents, Kolmogorov Complexity, Algorithmic Probability, Prediction, Inductive Behavior, Uncertainty Paper: http://agi-conference.org/2012/wp-content/uploads/2012/12/paper_7.pdf Presented by Alexey Potapov - other authors: Andrew Svitenkov and Yurii Vinogradov from AIDEUS, Russian Federation
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