One of the key challenges in AIXI approximation is model class approximation - i.e. how to meaningfully approximate Solomonoff Induction without requiring an infeasible amount of computation? This paper advocates a bottom-up approach to this problem, by describing a number of principled ensemble techniques for approximate AIXI agents. Each technique works by efficiently combining a set of existing environment models into a single, more powerful model. These techniques have the potential to play an important role in future AIXI approximations. © 2012 Springer-Verlag.
CITATION STYLE
Veness, J., Sunehag, P., & Hutter, M. (2012). On ensemble techniques for AIXI approximation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7716 LNAI, pp. 341–351). https://doi.org/10.1007/978-3-642-35506-6_35
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