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Imitation Learning in Robots

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Encyclopedia of the Sciences of Learning

Synonyms

Learning/programming from/by demonstration; Through apprenticeship

Definition

Imitation is the ability to recognize and reproduce others’ actions – By extension, imitation learning is a means of learning and developing new skills from observing these skills performed by another agent. Imitation learning (IL) as applied to robots is a technique to reduce the complexity of search spaces for learning. When observing either good or bad examples, one can reduce the search for a possible solution, by either starting the search from the observed good solution (local optima), or conversely, by eliminating from the search space what is known as a bad solution. Imitation learning offers an implicit means of training a machine, such that explicit and tedious programming of a task by a human user can be minimized or eliminated. Imitation learning is thus a “natural” means of training a machine, meant to be accessible to lay people.

Theoretical Background

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References

  • Argall, B. D., Chernova, S., Veloso, M., & Browning, B. (2009). A survey of robot learning from demonstration. Robotics and Autonomous Systems, 57(5), 469–483.

    Article  Google Scholar 

  • Billard, A., Calinon, S., Dillmann, R., & Schaal, S. (2008). Robot programming by demonstration. In B. Siciliano & O. Khatib (Eds.), Handbook of robotics. Cambridge, MA: MIT Press.

    Google Scholar 

  • Billing, E. A., & Hellstrm, T. (2010). A formalism for learning from demonstration. Paladyn, 1(1), 1–13.

    Article  Google Scholar 

  • Breazeal, C., & Scassellati, B. (2002). Robots that imitate humans. Trends in Cognitive Science, 6, 481–487.

    Article  Google Scholar 

  • Nehaniv, C. L., Ab, H. A., & Dautenhahn, K. (1999). Of hummingbirds and helicopters: An algebraic framework for interdisciplinary studies of imitation and its applications. In J. Demiris & A. Birk (Eds.), Interdisciplinary approaches to robot learning (pp. 136–161). Singapore: World Scientific Press.

    Google Scholar 

  • Schaal, S., Ijspeert, A., & Billard, A. (2003). Computational approaches to motor learning by imitation. Philosophical Transaction of the Royal Society of London, 358(1431), 537–547.

    Article  Google Scholar 

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Correspondence to Aude Billard .

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© 2012 Springer Science+Business Media, LLC

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Billard, A., Grollman, D. (2012). Imitation Learning in Robots. In: Seel, N.M. (eds) Encyclopedia of the Sciences of Learning. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-1428-6_758

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  • DOI: https://doi.org/10.1007/978-1-4419-1428-6_758

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4419-1427-9

  • Online ISBN: 978-1-4419-1428-6

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