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A Monte-Carlo AIXI Approximation

Veness, Joel; Ng, Kee Siong; Hutter, Marcus; Uther, William; Silver, David


This paper introduces a principled approach for the design of a scalable general reinforcement learning agent. Our approach is based on a direct approximation of AIXI, a Bayesian optimality notion for general reinforcement learning agents. Previously, it has been unclear whether the theory of AIXI could motivate the design of practical algorithms. We answer this hitherto open...[Show more]

CollectionsANU Research Publications
Date published: 2011-01
Type: Journal article
Source: Journal of Artificial Intelligence Research
DOI: 10.1613/jair.3125


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