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Consistency of Feature Markov Processes

Sunehag, Peter; Hutter, Marcus


We are studying long term sequence prediction (forecasting). We approach this by investigating criteria for choosing a compact useful state representation. The state is supposed to summarize useful information from the history. We want a method that is asymptotically consistent in the sense it will provably eventually only choose between alternatives that satisfy an optimality property related to the used criterion. We extend our work to the case where there is side information that one can...[Show more]

CollectionsANU Research Publications
Date published: 2010
Type: Conference paper
Source: Proceedings of International Conference on Algorithmic Learning Theory (ALT 2010)
DOI: 10.1007/978-3-642-16108-7_29


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