Context aware life pattern prediction using fuzzy-state Q-learning

Authors:
Mohamed Ali Feki;Sang Wan Lee;Zeungnam Bien;Mounir Mokhtari
Affiliations:
Institut Nationale des Télécommunications, Evry, France;Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea;Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea;Institut Nationale des Télécommunications, Evry, France
Venue:
ICOST'07 Proceedings of the 5th international conference on Smart homes and health telematics
Year:
2007

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Abstract

In an Assistive Eenvironment (AE), explicit/obtrusive interfaces for human/computer interaction can demand exclusive user attention and, often, replacement of them with implicit ones embedded into real-world artifacts for intuitive and unobtrusive use is desirable. As a part of solution, Context Aware can be utilized to recognize current context situation from a combination of low-level sensed contexts. Assuming the current context recognized, this paper tackles the next logical step of "the prediction of future contexts". This information allows the system to know patterns and their interrelations in user behaviour, which are not apparent at the lower levels of raw sensor data. The present paper analyzes prerequisites for user-centred prediction of future context and presents an algorithm for autonomous context recognition and prediction, based on our proposed Fuzzy-State Q- Learning technique as well as on some established methods for data-based prediction.