Committees are an important scenario for reaching consensus. Beyond standard consensus-seeking issues, committee decisions are complicated by a deadline, e.g., the next start date for a budget, or the start of a semester. In committee hiring decisions, it may be that if no candidate is supported by a strong majority, the default is to hire no one---an option that may cost committee members dearly. As a result, committee members might prefer to agree on a reasonable, if not necessarily the best, candidate, to avoid unfilled positions. In this paper we propose a model for the above scenario------based on a time-bounded iterative voting process. We explore theoretical features of CUDs, particularly focusing on convergence guarantees and quality of the final decision. An extensive experimental study demonstrates more subtle features of CUDs, e.g., the difference between two simple types of committee member behavior, lazy vs. proactive voters. Finally, a user study examines the differences between the behavior of rational voting bots and real voters, concluding that it may often be best to have bots play on the voters' behalf.
@cite_11 performed a study of human behavior in online voting. They classified voters into three distinct types, two of which are not strategic and one that will perform straightforward strategic moves. However their setting does not contain a deadline. Moreover, while they provide valuable insights on human voting patterns, they do not compare their framework with a rational strategic model, so the question of whether humans and bots act alike remained unanswered.
@cite_11
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Plurality voting is perhaps the most commonly used way to aggregate the preferences of multiple voters. The purpose of this paper is to provide a comprehensive study of people's voting behaviour in various online settings under the Plurality rule. Our empirical methodology consisted of a voting game in which participants vote for a single candidate out of a given set. We implemented voting games that replicate two common real-world voting scenarios: In the first, a single voter votes once after seeing a large pre-election poll. In the second game, several voters play simultaneously, and change their vote as the game progresses, as in small committees. The winning candidate in each game (and hence the subject's payment) is determined using the plurality rule. For each of these settings we generated hundreds of game instances, varying conditions such as the number of voters and their preferences. We show that people can be classified into at least three groups, two of which are not engaged in any strategic behavior. The third and largest group tends to select the natural "default" action when there is no clear strategic alternative. When an active strategic decision can be made that improves their immediate payoff, people usually choose that strategic alternative. Our study has insight for multi-agent system designers in uncovering patterns that provide reasonable predictions of voters' behaviors, which may facilitate the design of agents that support people or act autonomously in voting systems.