Encyclopedia of Machine Learning and Data Mining

2017 Edition
| Editors: Claude Sammut, Geoffrey I. Webb

Locally Weighted Regression for Control

  • Jo-Anne TingEmail author
  • Franzisk Meier
  • Sethu Vijayakumar
  • Stefan Schaal
Reference work entry
DOI: https://doi.org/10.1007/978-1-4899-7687-1_493



This entry addresses two topics:  learning control and locally weighted regression.

 Learning control refers to the process of acquiring a control strategy for a particular control system and a particular task by trial and error. It is usually distinguished from adaptive control (Aström and Wittenmark 1989) in that the learning system is permitted to fail during the process of learning, resembling how humans and animals acquire new movement strategies. In contrast, adaptive control emphasizes single-trial convergence without failure, fulfilling stringent performance constraints, e.g., as needed in life-critical systems like airplanes and industrial robots.

Locally weighted regression refers to  supervised learning of continuous functions (otherwise known as function approximation or  regression) by means of spatially...
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Recommended Reading

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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Jo-Anne Ting
    • 1
    Email author
  • Franzisk Meier
    • 2
  • Sethu Vijayakumar
    • 1
    • 2
  • Stefan Schaal
    • 3
    • 4
  1. 1.University of EdinburghEdinburghUK
  2. 2.University of Southern CaliforniaLos AngelesUSA
  3. 3.Max Planck Institute for Intelligent SystemsStuttgartGermany
  4. 4.Computer ScienceUniversity of Southern CaliforniaLos AngelesUSA