Corpus ID: 3661007

Decomposition Strategies for Constructive Preference Elicitation

@article{Dragone2018DecompositionSF,
  title={Decomposition Strategies for Constructive Preference Elicitation},
  author={Paolo Dragone and Stefano Teso and Mohit Kumar and Andrea Passerini},
  journal={ArXiv},
  year={2018},
  volume={abs/1711.08247}
}
We tackle the problem of constructive preference elicitation, that is the problem of learning user preferences over very large decision problems, involving a combinatorial space of possible outcomes. In this setting, the suggested configuration is synthesized on-the-fly by solving a constrained optimization problem, while the preferences are learned itera tively by interacting with the user. Previous work has shown that Coactive Learning is a suitable method for learning user preferences in… Expand
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