Encyclopedia of Machine Learning

2010 Edition
| Editors: Claude Sammut, Geoffrey I. Webb

Preference Learning

  • Johannes Fürnkranz
  • Eyke Hüllermeier
Reference work entry
DOI: https://doi.org/10.1007/978-0-387-30164-8_662



Preference learning refers to the task of learning to predict an order relation on a collection of objects (alternatives). In the training phase, preference learning algorithms have access to examples for which the sought order relation is (partially) known. Depending on the formal modeling of the preference context and the alternatives to be ordered, one can distinguish between object ranking problems and label ranking problems. Both types of problems can be approached in two fundamentally different ways, either by modeling the binary preference relation directly, or by inducing this relation indirectly via an underlying (latent) utility function.

Motivation and Background

Preference information plays a key role in automated decision making and appears in various guises in Artificial Intelligence (AI) research, notably in fields such as agents, non-monotonic reasoning, constraint satisfaction, planning, and qualitative decision theory...

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Recommended Reading

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Johannes Fürnkranz
    • 1
  • Eyke Hüllermeier
    • 2
  1. 1.TU DarmstadtDarmstadtGermany
  2. 2.Philipps-Universität MarburgMarburgGermany