Learning from Humans

  • Aude G. BillardEmail author
  • Sylvain Calinon
  • Rüdiger Dillmann
Part of the Springer Handbooks book series (SHB)


This chapter surveys the main approaches developed to date to endow robots with the ability to learn from human guidance. The field is best known as robot programming by demonstration, robot learning from/by demonstration, apprenticeship learning and imitation learning. We start with a brief historical overview of the field. We then summarize the various approaches taken to solve four main questions: when, what, who and when to imitate. We emphasize the importance of choosing well the interface and the channels used to convey the demonstrations, with an eye on interfaces providing force control and force feedback. We then review algorithmic approaches to model skills individually and as a compound and algorithms that combine learning from human guidance with reinforcement learning. We close with a look on the use of language to guide teaching and a list of open issues.


Reinforcement Learning Humanoid Robot Reward Function Haptic Device Incremental Learning 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



artificial neural network


elementary operator


hidden Markov model


human–robot interaction


inverse reinforcement learning


learning from demonstration

learning from human demonstration


machine learning


programming by demonstration


partially observable Markov decision process


radial basis function network


reinforcement learning


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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Aude G. Billard
    • 1
    Email author
  • Sylvain Calinon
    • 2
  • Rüdiger Dillmann
    • 3
  1. 1.School of EngineeringSwiss Federal Institute of Technology (EPFL)LausanneSwitzerland
  2. 2.Idiap Research InstituteMartignySwitzerland
  3. 3.Institute for Technical InformaticsKarlsruhe Institute of TechnologyKarlsruheGermany

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