Context Feature Learning through Deep Learning for Adaptive Context-Aware Decision Making in the Home
Résumé
In Intelligent Environments, prediction and decision
must take the context of interaction into account to adapt
themselves to the evolving environment. If most of the approaches
to deal with this problem have used a formal representation
of context, we present in this paper a direct extraction of the
context from raw sensor data using deep neural network and
reinforcement learning. Experiments undertaken in a voice con-
trolled smart home showed which elements are useful to perform
context-aware decision-making in the home and the adequacy of
reinforcement learning to tackle an evolving environment.
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