Issue No. 01 - January/February (2007 vol. 22)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MIS.2007.15
Karthik Gopalratnam , University of Texas at Arlington
Diane J. Cook , Washington State University
Prediction is important in various domains. Intelligent systems that can predict future events can make more informed, and therefore more reliable, decisions. Active LeZi, an online sequential prediction algorithm that can reason about the future in stochastic domains, uses an information-theoretic approach to analyze synthetic data, UNIX command data, and sequential data obtained from the MavHome smart home environment.
sequential prediction, smart environments, Active LeZi, MavHome
D. J. Cook and K. Gopalratnam, "Online Sequential Prediction via Incremental Parsing: The Active LeZi Algorithm," in IEEE Intelligent Systems, vol. 22, no. , pp. 52-58, 2007.