Consistency of Feature Markov Processes

Details Consistency of Feature Markov Processes Consistency of Feature Markov Processes

2010-07-13

arxiv.org/abs/1007.2075v1

Proc. 21st International Conf. on Algorithmic Learning Theory (ALT-2010) pages 360-374

Computer Science

Learning

16 LaTeX pages

Scientific paper

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 take advantage of and, furthermore, we briefly discuss the active setting where an agent takes actions to achieve desirable outcomes.

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