Extending choice assessments to choice functions: An algorithm for computing the natural extension
<|reference_start|>Extending choice assessments to choice functions: An algorithm for computing the natural extension: We study how to infer new choices from prior choices using the framework of choice functions, a unifying mathematical framework for decision-making based on sets of preference orders. In particular, we define the natural (most conservative) extension of a given choice assessment to a coherent choice function -- whenever possible -- and use this natural extension to make new choices. We provide a practical algorithm for computing this natural extension and various ways to improve scalability. Finally, we test these algorithms for different types of choice assessments.<|reference_end|>
@article{decadt2024extending,
    title={Extending choice assessments to choice functions: An algorithm for
  computing the natural extension},
    author={Arne Decadt and Alexander Erreygers and Jasper De Bock},
    journal={arXiv preprint arXiv:2407.21164},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.21164},
    primaryClass={cs.AI math.PR}
}