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Synchronizing to the Environment: Information Theoretic Constraints on Agent Learning
[article]
2001
arXiv
pre-print
We show that the way in which the Shannon entropy of sequences produced by an information source converges to the source's entropy rate can be used to monitor how an intelligent agent builds and effectively uses a predictive model of its environment. We introduce natural measures of the environment's apparent memory and the amounts of information that must be (i) extracted from observations for an agent to synchronize to the environment and (ii) stored by an agent for optimal prediction. If
arXiv:nlin/0103038v1
fatcat:z3ce5e24rzaibp2cavsr7ogblq