Papers
PUBLISHED:
2021 “Reaching consensus under a deadline” M Bannikova, L Dery, S Obraztsova, Z Rabinovich, JS Rosenschein
Autonomous Agents and Multi-Agent Systems 35 (1), 1-42
Group decisions are often complicated by a deadline. For example, in committee hiring decisions the deadline might be the next start of a budget, or the beginning of a semester. 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 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—Consensus Under a Deadline (CUD)—based on a time-bounded iterative voting process. We provide convergence guarantees and an analysis of the 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.
Games. 12. 76. 10.3390/g12040076.
This paper proposes a model of a legislature, formed by several parties, which has to vote for or against a certain bill in the presence of a lobbyist interested in a certain vote outcome. We show that the ease with which the lobbyist can manipulate a legislature decision increases with the number of elected parties, and, consequently, decreases with an electoral threshold. On the other hand, a lower electoral threshold increases the representativeness of a legislature. We combine these two effects in a notion of fairness. We show the existence of an electoral threshold that optimizes the fairness of a political system, which is close to 1–5%. Namely, the optimal threshold (in our sense) is close to thresholds that exist in most parliamentary democracies.
IN PROCEEDINGS:
2017 “Haste makes waste: a case to favour voting bots” D Ben Yosef, L Naamani-Dery, S Obraztsova, Z Rabinovich, and M Bannikova.
In Proceedings of the International Conference on Web Intelligence (WI '17). Association for Computing Machinery, New York, NY, USA, 419–425.
Voting is a common way to reach a group decision. When possible, voters will attempt to vote strategically, in order to optimize their satisfaction from the outcome. Previous research has modelled how rational voter agents (bots) vote to maximize their personal utility in an iterative voting process that has a deadline (a timeout). However, it remains an open question whether human beings behave rationally when faced with the same settings. The focus of this paper is therefore to examine how the deadline factor affects manipulative behavior in real-world scenarios were humans are required to reach a decision before a deadline. An On-line platform was built to enable voting games by all types of users: agents (bots), humans, and mixed games with both humans and agents. We compare the results of human behavior and bot behavior and conclude that it might be wise to allow bots to make (certain) decisions on our behalf.
2016 “Between fairness and a mistrial: Consensus under a deadline” M Bannikova, L Naamani-Dery, S Obraztsova, Z Rabinovich, J S Rosenschein
The 10th workshop on advances in preference handling (M-PREF). New-York, USA.
Jury trial is, perhaps, the most prominent example of seeking a consensus. The process is particularly difficult if the judge places a deadline by which the jury must reach a unanimous decision, otherwise declaring a mistrial. A mistrial is commonly perceived to be worse than any decision the jury might render. As a result, while each juror has her own idea about the fairness of each possible trial outcome, she may eventually choose to vote for a less fair outcome, rather than cause a mistrial by breaking unanimity. In this paper we propose a model for the above scenario — Consensus Under a Deadline (CUD) — based on a time-bounded iterative voting process. We provide some theoretical features of CUDs, particularly focusing on convergence guarantees and the quality of the final decision. An extensive experimental study demonstrates the more subtle features of CUDs, e.g., the difference between two simple types of juror behaviour, lazy vs. proactive voters.
Proceedings of 15th International Conference on Group Decision and Negotiation, pp.207–214.
Two voters must choose between two alternatives. Voters vote in a fixed linear order. If there is not unanimity for any alternative, the procedure is repeated. At every stage, each voter prefers the same alternative to the other, has utilities decreasing with stages, and has an impatience degree representing when it is worth voting for the non-preferred alternative now rather than waiting for the next stage and voting for the preferred alternative. Intuition suggests that the more patient voter will get his preferred alternative. I found that in the unique solution of the sequential voting procedure obtained by backward induction, the first voter get his preferred alternative at the first stage independently from his impatience rate.