Binary Aggregation by Selection of the Most Representative Voters

Examples range from multiagent planning, That is, we look for the most representative voter and return to crowdsourcing and human computation, to collaborative her ballot as the outcome. In our example, a natural choice filtering for recommender systems, to rank aggregation would be any of the voters voting (0, 1, 1). The distance of for search engines, to coordination and resource allocation this choice to the individual ballots is 42 (21 voters disagree in multiagent systems. Several frameworks have been on 2 issues each), i.e., this solution is only marginally worse proposed in the literature on computational social choice than the solution returned by the distance-based rule--and it (Chevaleyre et al. 2007; Brandt, Conitzer, and Endriss 2013) is optimal in case (1, 1, 1) is infeasible.