Egalitarian Deliberative Decision Making
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We study a scenario in which an agent population wishes to identify a majority-supported proposal to change the status quo, where proposals are elements of an abstract space. In our deliberation process agents form coalitions around proposals that they prefer over the status quo, and can then join forces to create larger coalitions by merging two coalitions around a new proposal, possibly leaving dissenting agents behind. We identify a class of metric spaces, which includes all Euclidean spaces, for which the deliberation process is guaranteed to result in success: Deliberation will terminate with a majority coalition, as long as a majority-supported proposal exists. We then consider a more general proposal space where deliberation might not be successful. For such a setting we study sufficient conditions on the type of deliberation that can again guarantee success. We complement our analysis with a centralized dynamic programming algorithm to identify the most-supported proposal.
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