Fuzzy-state Q-learning-based human behavior suggestion system in intelligent sweet home

Cited 2 time in webofscience Cited 0 time in scopus
  • Hit : 118
  • Download : 0
Memory impaired people, e.g., dementia people, requires careful social support. Dementia people are getting increased with very high rate especially. It has been reported that regular daily life can alleviate the symptom of the memory loss. Accordingly, human behavior suggestion is highly expected to help memory impaired people live regularly. In this paper, we propose a human behavior suggestion system based on Fuzzy-state Q-Learning for memory impaired person, and show its possible application in Intelligent Sweet Home. Specifically, we claim that an averaged frequency feature is an important factor. In order to evaluate the validity of the proposed human behavior suggestion system, we conduct experiments with a real world data set, INT DB. The experimental results show that the proposed system with the averaged frequency feature outperforms the existing system. ©2009 IEEE.
Publisher
IEEE
Issue Date
2008-08
Language
English
Citation

2009 IEEE International Conference on Fuzzy Systems, pp.283 - 287

DOI
10.1109/FUZZY.2009.5277166
URI
http://hdl.handle.net/10203/244252
Appears in Collection
BiS-Conference Papers(학술회의논문)
Files in This Item
There are no files associated with this item.
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 2 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0