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On the computability of solomonoff induction and knowledge-seeking

Leike, Jan; Hutter, Marcus

Description

Solomonoff induction is held as a gold standard for learning, but it is known to be incomputable. We quantify its incomputability by placing various flavors of Solomonoff’s prior M in the arithmetical hierarchy. We also derive computability bounds for knowledge-seeking agents, and give a limit-computable weakly asymptotically optimal reinforcement learning agent.

CollectionsANU Research Publications
Date published: 2015
Type: Conference paper
URI: http://hdl.handle.net/1885/103397
Source: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
DOI: 10.1007/978-3-319-24486-0_24

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