A tutorial on hidden Markov models and selected applications in speech recognition
Readings in speech recognition
Machine Learning
Smart Office: Design of an Intelligent Environment
IEEE Intelligent Systems
Learning Logical Definitions from Relations
Machine Learning
Machine Learning
Perceptual Components for Context Aware Computing
UbiComp '02 Proceedings of the 4th international conference on Ubiquitous Computing
Learning to Detect User Activity and Availability from a Variety of Sensor Data
PERCOM '04 Proceedings of the Second IEEE International Conference on Pervasive Computing and Communications (PerCom'04)
The KidsRoom: A Perceptually-Based Interactive and Immersive Story Environment
Presence: Teleoperators and Virtual Environments
The lumière project: Bayesian user modeling for inferring the goals and needs of software users
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Easing the Smart Home: Translating Human Hierarchies to Intelligent Environments
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
Group interaction analysis in dynamic context
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on human computing
Learning situation models in a smart home
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on human computing
Integral framework for acquiring and evolving situations in smart environments
Journal of Ambient Intelligence and Smart Environments
Learning patterns in ambient intelligence environments: a survey
Artificial Intelligence Review
Computing with instinct
Intrinsically motivated intelligent sensed environments
EG-ICE'06 Proceedings of the 13th international conference on Intelligent Computing in Engineering and Architecture
Application of decision trees to smart homes
Designing Smart Homes
Designing Izbushka: Investigating Interactions in Context Zero Environments
International Journal of Agent Technologies and Systems
Inferring ECA-based rules for ambient intelligence using evolutionary feature extraction
Journal of Ambient Intelligence and Smart Environments
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This paper addresses the problem of supervised learning in intelligent environments. An intelligent environment perceives user activity and offers a number of services according to the perceived information about the user. An abstract context model in the form of a situation network is used to represent the intelligent environment, its occupants and their activities. The context model consists of situations, roles played by entities and relations between these entities. The objective is to adapt the system services, which are associated to the situations of the model, to the changing needs of the user. For this, a supervisor gives feedback by correcting system services that are found to be inappropriate to user needs. The situation network can be developed by exchanging the system service-situation association, by splitting the situation, or by learning new roles. The situation split is interpreted as a replacement of the former situation by sub-situations whose number and characteristics are determined using conceptual or decision tree algorithms. Different algorithms have been tested on a context model within the SmartOffice environment of the PRIMA research group. The decision tree algorithm (ID3) has been found to give the best results.