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Online Sequential Prediction via Incremental Parsing: The Active LeZi Algorithm

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2 Author(s)
Gopalratnam, K. ; Texas Univ., Arlington, TX ; Cook, D.J.

Intelligent systems that can predict future events can make more reliable decisions. Active LeZi, a sequential prediction algorithm, can reason about the future in stochastic domains without domain-specific knowledge. In this article, potential of constructing a prediction algorithm based on data compression techniques are investigated. Active LeZi prediction algorithm approaches sequential prediction from an information-theoretic standpoint. For any sequence of events that can be modeled as a stochastic process, ALZ uses Markov models to optimally predict the next symbol

Published in:

Intelligent Systems, IEEE  (Volume:22 ,  Issue: 1 )