IJCAI 2018
Accountable Approval Sorting
Abstract
We consider decision situations in which a set of points of view (voters, criteria) are to sort a set of candidates to ordered categories (Good/Bad). Candidates are judged good, when approved by a sufficient set of points of view; this corresponds to NonCompensatory Sorting. To be accountable, such approval sorting should provide guarantees about the decision process and decisions concerning specific candidates. We formalize accountability using a feasibility problem expressed as a boolean satisfiability formulation. We illustrate different forms of accountability when a committee decides with approval sorting and study the information that should be disclosed by the committee.
Authors
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Context
- Venue
- International Joint Conference on Artificial Intelligence
- Archive span
- 1969-2025
- Indexed papers
- 14525
- Paper id
- 781174642125947640