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It would be nice to have two more probabilistic methods:
Conditional Utilitarian Rule
- Input: approval ballots.
- Output: probability distribution.
- A non-abstaining ballot is one that approves at least one candidate.
- P(candidate x) = probability arising from the following random process:
- score(candidate x) = number of approvals for x
- Draw a ballot uniformly at random.
- Let A be the set of candidates approved on that ballot.
- Let M be the subset of A with largest score.
- Draw a member of A uniformly at random.
Maximum Partial Consensus (MaxParC)
- Input: ratings ballots (a "UtilityProfile") with ratings between 0 and 100 (inclusive)
- Output: probability distribution.
- Procedure:
- Let u(i,x) be the rating ("utility") voter i assigned to candidate x.
- Let r(i,x) = 100 if u(i,x) >= u(i,y) for all candidates y, otherwise let r(i,x) = u(i,x)
- This ensures max{ r(i,x) : x } = 100
- Let N be the number of voters.
- For each x, find the smallest integer m in {0,...N} so that |{ i : r(i,x)/100 > m/N }| >= N - m. Denote this value t(x).
- Construct an approval profile as follows:
- i approves x iff r(i,x)/100 > m/N
- Apply the following version of the Conditional Utilitarian Rule to this approval profile:
- score(candidate x) = number of approvals for x + (avg. u(i,x) over all voters i) / 101
- Draw a ballot uniformly at random.
- Let A be the set of candidates approved on that ballot.
- Let M be the subset of A with largest score.
- Draw a member of A uniformly at random.
Reference: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3751225 (accepted for Soc Choice Welf)
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