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Learning User Preferences in Ubiquitous Systems: A User Study and a Reinforcement Learning Approach

  • Sofia Zaidenberg
  • Patrick Reignier
  • Nadine Mandran
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 339)

Abstract

Our study concerns a virtual assistant, proposing services to the user based on its current perceived activity and situation (ambient intelligence). Instead of asking the user to define his preferences, we acquire them automatically using a reinforcement learning approach. Experiments showed that our system succeeded the learning of user preferences. In order to validate the relevance and usability of such a system, we have first conducted a user study. 26 non-expert subjects were interviewed using a model of the final system. This paper presents the methodology of applying reinforcement learning to a real-world problem with experimental results and the conclusions of the user study.

Keywords

Ambient Intelligence Context-aware Computing Personnal Assistant Reinforcement Learning User Study 

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Copyright information

© IFIP 2010

Authors and Affiliations

  • Sofia Zaidenberg
    • 1
  • Patrick Reignier
    • 1
  • Nadine Mandran
    • 2
  1. 1.INRIA 
  2. 2.LIG 

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