Synchronizing to the Environment: Information Theoretic Constraints on Agent Learning

Details Synchronizing to the Environment: Information Theoretic Constraints on Agent Learning Synchronizing to the Environment: Information Theoretic Constraints on Agent Learning

2001-03-23

arxiv.org/abs/nlin/0103038v1

Nonlinear Sciences

Adaptation and Self-Organizing Systems

6 pages, 5 figures, Santa Fe Institute Working Paper 01-03-020, http://www.santafe.edu/projects/CompMech/papers/stte.html

Scientific paper

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 structural properties are ignored, the missed regularities are converted to apparent randomness. Conversely, using representations that assume too much memory results in false predictability.

Affiliated with

Also associated with

No associations

Rating

Synchronizing to the Environment: Information Theoretic Constraints on Agent Learning does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Synchronizing to the Environment: Information Theoretic Constraints on Agent Learning, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Synchronizing to the Environment: Information Theoretic Constraints on Agent Learning will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-192954