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Principles and experimentations of self-organizing embedded agents allowing learning from demonstration in ambient robotics

Journal Article


Abstract


  • Ambient systems are populated by many heterogeneous devices to provide adequate services to their users. The adaptation of an ambient system to the specific needs of its users is a challenging task. Because human–system interaction has to be as natural as possible, we propose an approach based on Learning from Demonstration (LfD). LfD is an interesting approach to generalize what has been observed during the demonstration to similar situations. However, using LfD in ambient systems needs adaptivity of the learning technique. We present ALEX, a multi-agent system able to dynamically learn and reuse contexts from demonstrations performed by a tutor. The results of the experiments performed on both a real and a virtual robot show interesting properties of our technology for ambient applications.

Authors


  •   Verstaevel, Nicolas
  •   Regis, Christine (external author)
  •   Gleizes, Marie-Pierre (external author)
  •   Robert, Fabrice (external author)

Publication Date


  • 2016

Geographic Focus


Citation


  • Verstaevel, N., Regis, C., Gleizes, M. & Robert, F. (2016). Principles and experimentations of self-organizing embedded agents allowing learning from demonstration in ambient robotics. Future Generation Computer Systems: the international journal of grid computing: theory, methods and applications, 64 78-87.

Scopus Eid


  • 2-s2.0-84963850942

Number Of Pages


  • 9

Start Page


  • 78

End Page


  • 87

Volume


  • 64

Place Of Publication


  • Netherlands

Abstract


  • Ambient systems are populated by many heterogeneous devices to provide adequate services to their users. The adaptation of an ambient system to the specific needs of its users is a challenging task. Because human–system interaction has to be as natural as possible, we propose an approach based on Learning from Demonstration (LfD). LfD is an interesting approach to generalize what has been observed during the demonstration to similar situations. However, using LfD in ambient systems needs adaptivity of the learning technique. We present ALEX, a multi-agent system able to dynamically learn and reuse contexts from demonstrations performed by a tutor. The results of the experiments performed on both a real and a virtual robot show interesting properties of our technology for ambient applications.

Authors


  •   Verstaevel, Nicolas
  •   Regis, Christine (external author)
  •   Gleizes, Marie-Pierre (external author)
  •   Robert, Fabrice (external author)

Publication Date


  • 2016

Geographic Focus


Citation


  • Verstaevel, N., Regis, C., Gleizes, M. & Robert, F. (2016). Principles and experimentations of self-organizing embedded agents allowing learning from demonstration in ambient robotics. Future Generation Computer Systems: the international journal of grid computing: theory, methods and applications, 64 78-87.

Scopus Eid


  • 2-s2.0-84963850942

Number Of Pages


  • 9

Start Page


  • 78

End Page


  • 87

Volume


  • 64

Place Of Publication


  • Netherlands