Automation Intelligence for the Smart Environment

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.

Cite

Text

Youngblood et al. "Automation Intelligence for the Smart Environment." International Joint Conference on Artificial Intelligence, 2005.

Markdown

[Youngblood et al. "Automation Intelligence for the Smart Environment." International Joint Conference on Artificial Intelligence, 2005.](https://mlanthology.org/ijcai/2005/youngblood2005ijcai-automation/)

BibTeX

@inproceedings{youngblood2005ijcai-automation,
  title     = {{Automation Intelligence for the Smart Environment}},
  author    = {Youngblood, G. Michael and Iii, Edwin O. Heierman and Holder, Lawrence B. and Cook, Diane J.},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2005},
  pages     = {1513-1514},
  url       = {https://mlanthology.org/ijcai/2005/youngblood2005ijcai-automation/}
}