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Approximating Common Voting Rules by Sequential Voting in Multi-Issue Domains
International Symposium on Artificial Intelligence and Mathematics
When agents need to make decisions on multiple issues, one solution is to vote on the issues sequentially. In this paper, we investigate how well the winner under the sequential voting process approximates the winners under some common voting rules. Some common voting rules, including Borda, k-approval, Copeland, maximin, Bucklin, and Dodgson, admit natural scoring functions that can serve as a basis for approximation results. We focus on multi-issue domains where each issue is binary and thedblp:conf/isaim/XiaC12 fatcat:unnvu245vvex5abwocvnogyxay