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Communication Dans Un Congrès Année : 2009

Learning Conditional Preference Networks with Queries

Résumé

We investigate the problem of eliciting CP-nets in the well-known model of exact learning with equivalence and membership queries. The goal is to identify a preference ordering with a binary-valued CP-net by guiding the user through a sequence of queries. Each example is a dominance test on some pair of outcomes. In this setting, we show that acyclic CP-nets are not learnable with equivalence queries alone, while they are learnable with the help of membership queries if the supplied examples are restricted to swaps. A similar property holds for tree CP-nets with arbitrary examples. In fact, membership queries allow us to provide attribute- efficient algorithms for which the query complexity is only logarithmic in the number of attributes. Such results highlight the utility of this model for eliciting CP-nets in large multi-attribute domains.
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Dates et versions

hal-00944391 , version 1 (12-02-2014)

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  • HAL Id : hal-00944391 , version 1

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Frédéric Koriche, Bruno Zanuttini. Learning Conditional Preference Networks with Queries. Proc. 21th International Joint Conference Artificial Intelligence (IJCAI2009), Jul 2009, United States. 6 p. ⟨hal-00944391⟩
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