Do people want smarter ballots?

We ascertain whether citizens want to have smart ballots, that is, whether they appreciate having the possibility to express some support for more than one option (expression across options) and to indicate different levels of support for these options (expression within options). We conducted two independent yet complementary survey experiments at the time of the Super Tuesday Democratic primaries to examine which voting method citizens prefer, one with the real candidates in the states holding Democratic primaries and one with fictitious candidates in the whole country. In both surveys, respondents were asked to vote using four different voting rules: single, approval, rank, and point (score). After they cast their vote, respondents were asked how satisfied they were using each voting method. The findings are consistent in both studies: the single vote is the most preferred voting method. We show that this is a reflection of a status quo bias, as citizens’ views are strongly correlated with age.

Complexity of Shift Bribery in Committee Elections

Given an election, a preferred candidate p , and a budget, the S HIFT B RIBERY problem asks whether p can win the election after shifting p higher in some voters’ preference orders. Of course, shifting comes at a price (depending on the voter and on the extent of the shift) and one must not exceed the given budget. We study the (parameterized) computational complexity of S HIFT B RIBERY for multiwinner voting rules where winning the election means to be part of some winning committee. We focus on the well-established SNTV, Bloc, k -Borda, and Chamberlin-Courant rules, as well as on approximate variants of the Chamberlin-Courant rule. We show that S HIFT B RIBERY tends to be harder in the multiwinner setting than in the single-winner one by showing settings where S HIFT B RIBERY is computationally easy in the single-winner cases, but is hard (and hard to approximate) in the multiwinner ones.

Eliciting Fairness in N-Player Network Games through Degree-Based Role Assignment

From social contracts to climate agreements, individuals engage in groups that must collectively reach decisions with varying levels of equality and fairness. These dilemmas also pervade distributed artificial intelligence, in domains such as automated negotiation, conflict resolution, or resource allocation, which aim to engineer self-organized group behaviors. As evidenced by the well-known Ultimatum Game, where a Proposer has to divide a resource with a Responder, payoff-maximizing outcomes are frequently at odds with fairness. Eliciting equality in populations of self-regarding agents requires judicious interventions. Here, we use knowledge about agents’ social networks to implement fairness mechanisms, in the context of Multiplayer Ultimatum Games. We focus on network-based role assignment and show that attributing the role of Proposer to low-connected nodes increases the fairness levels in a population. We evaluate the effectiveness of low-degree Proposer assignment considering networks with different average connectivities, group sizes, and group voting rules when accepting proposals (e.g., majority or unanimity). We further show that low-degree Proposer assignment is efficient, in optimizing not only individuals’ offers but also the average payoff level in the population. Finally, we show that stricter voting rules (i.e., imposing an accepting consensus as a requirement for collectives to accept a proposal) attenuate the unfairness that results from situations where high-degree nodes (hubs) play as Proposers. Our results suggest new routes to use role assignment and voting mechanisms to prevent unfair behaviors from spreading on complex networks.

Comparative International Fisheries Management

High-seas fisheries are managed by a set of approximate 20 regional fisheries management organizations (RFMOs) that vary in terms of membership, structure, processes, and health of the stocks they manage. These RFMOs have tackled similar challenges in sometimes different and sometimes convergent ways, learning from each other and occasionally collaborating. This chapter gives an overview of the difficulties of international fisheries management; the primary regulatory approaches (and their evolution) in these organizations, such as voting rules and options to opt out of collective regulations; and the efforts to monitor and enforce rules that have been created. Individually and sometimes collectively RFMOs have worked to decrease the ability of states or vessels to fish outside of the regulatory process, including making it difficult for fish caught outside of RFMO rules to find markets, and they have increased the ability to monitor compliance. While some scholars argue that the regional nature of fisheries management causes problems and that there should be fewer organizations regulating international fisheries, RFMOs have resisted consolidation or management collaboration. Ultimately there is still much to be learned about the sources of effectiveness in management of high-seas fisheries.

Strategyproof Randomized Social Choice for Restricted Sets of Utility Functions

When aggregating preferences of multiple agents, strategyproofness is a fundamental requirement. For randomized voting rules, so-called social decision schemes (SDSs), strategyproofness is usually formalized with the help of utility functions. A classic result shown by Gibbard in 1977 characterizes the set of SDSs that are strategyproof with respect to all utility functions and shows that these SDSs are either indecisive or unfair. For finding more insights into the trade-off between strategyproofness and decisiveness, we propose the notion of U-strategyproofness which requires that only voters with a utility function in the set U cannot manipulate. In particular, we show that if the utility functions in U value the best alternative much more than other alternatives, there are U-strategyproof SDSs that choose an alternative with probability 1 whenever all but k voters rank it first. We also prove for rank-based SDSs that this large gap in the utilities is required to be strategyproof and that the gap must increase in k. On the negative side, we show that U-strategyproofness is incompatible with Condorcet-consistency if U satisfies minimal symmetry conditions and there are at least four alternatives. For three alternatives, the Condorcet rule can be characterized based on U-strategyproofness for the set U containing all equi-distant utility functions.

Even More Effort Towards Improved Bounds and Fixed-Parameter Tractability for Multiwinner Rules

Multiwinner elections have proven to be a fruitful research topic with many real world applications. We contribute to this line of research by improving the state of the art regarding the computational complexity of computing good committees. More formally, given a set of candidates C, a set of voters V, each ranking the candidates according to their preferences, and an integer k; a multiwinner voting rule identifies a committee of size k, based on these given voter preferences. In this paper we consider several utilitarian and egailitarian OWA (ordered weighted average) scoring rules, which are an extensively researched family of rules (and a subfamily of the family of committee scoring rules). First, we improve the result of Betzler et al. [JAIR, 2013], which gave a O(n^n) algorithm for computing winner under the Chamberlin Courant rule (CC), where n is the number of voters; to a running time of O(2^n), which is optimal. Furthermore, we study the parameterized complexity of the Pessimist voting rule and describe a few tractable and intractable cases. Apart from such utilitarian voting rules, we extend our study and consider egalitarian median and egalitarian mean (both committee scoring rules), showing some tractable and intractable results, based on nontrivial structural observations.

Inducing Cooperation through Weighted Voting and Veto Power

We study the design of voting rules for committees representing heterogeneous groups (countries, states, districts) when cooperation among groups is voluntary. While efficiency recommends weighting groups proportionally to their stakes, we show that accounting for participation constraints entails overweighting some groups, those for which the incentive to cooperate is the lowest. When collective decisions are not enforceable, cooperation induces more stringent constraints that may require granting veto power to certain groups. In the benchmark case where groups differ only in their population size (i.e., the apportionment problem), the model provides a rationale for setting a minimum representation for smaller groups. (JEL C73, D71, D72)

Towards completing the puzzle: complexity of control by replacing, adding, and deleting candidates or voters

We investigate the computational complexity of electoral control in elections. Electoral control describes the scenario where the election chair seeks to alter the outcome of the election by structural changes such as adding, deleting, or replacing either candidates or voters. Such control actions have been studied in the literature for a lot of prominent voting rules. We complement those results by solving several open cases for Copeland$$^{\alpha }$$ α , maximin, k-veto, plurality with runoff, veto with runoff, Condorcet, fallback, range voting, and normalized range voting.

An analytical and experimental comparison of maximal lottery schemes

Maximal lottery ($$ ML $$ ML ) schemes constitute an interesting class of randomized voting rules that were proposed by Peter Fishburn in 1984 and have been repeatedly recommended for practical use. However, the subtle differences between different $$ ML $$ ML schemes are often overlooked. Two canonical subsets of $$ ML $$ ML schemes are "Image missing" schemes (which only depend on unweighted majority comparisons) and "Image missing" schemes (which only depend on weighted majority comparisons). We prove that "Image missing" schemes are the only homogeneous $$ ML $$ ML schemes that satisfy $$ SD $$ SD -efficiency and $$ SD $$ SD -participation, but are also among the most manipulable $$ ML $$ ML schemes. While all $$ ML $$ ML schemes are manipulable and even violate monotonicity, they are never manipulable when a Condorcet winner exists and satisfy a relative notion of monotonicity. We also evaluate the frequency of manipulable preference profiles and the degree of randomization of $$ ML $$ ML schemes via extensive computer simulations. In summary, $$ ML $$ ML schemes are rarely manipulable and often do not randomize at all, especially for few alternatives. The average degree of randomization of "Image missing" schemes is consistently lower than that of "Image missing" schemes.