Automation intelligence for the smart environment

Authors:
G. Michael Youngblood;Edwin O. Heierman;Lawrence B. Holder;Diane J. Cook
Affiliations:
Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX;Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX;Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX;Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX
Venue:
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Year:
2005

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Abstract

Scaling AI algorithms to large problems requires that these algorithms work together to harness their respective strengths. We introduce a method of automatically constructing HHMMs using the output of a sequential data-mining algorithm and sequential prediction algorithm. We present the theory of this technique and demonstrate results using the MavHome intelligent environment.