On ensemble techniques for AIXI approximation
Date
2012
Authors
Veness, Joel
Sunehag, Peter
Hutter, Marcus
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Conference Organising Committee
Abstract
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.
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Keywords: Bottom up approach; Ensemble techniques; Environment models; Artificial intelligence
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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
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Conference paper
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2037-12-31
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