Information aggregation and communication in committees

Lu and Boutilier proposed a novel approach based on "minimax regret" to use classical score based voting rules in the setting where preferences can be any partial (instead of complete) orders over the set of alternatives. We show here that such an approach is vulnerable to a new kind of manipulation which was not present in the classical (where preferences are complete orders) world of voting. We call this attack "manipulative elicitation." More specifically, it may be possible to (partially) elicit the preferences of the agents in a way that makes some distinguished alternative win the election who may not be a winner if we elicit every preference completely. More alarmingly, we show that the related computational task is polynomial time solvable for a large class of voting rules which includes all scoring rules, maximin, Copeland α for every α ∈ [0,1], simplified Bucklin voting rules, etc. We then show that introducing a parameter per pair of alternatives which specifies the minimum number of partial preferences where this pair of alternatives must be comparable makes the related computational task of manipulative elicitation NP-complete for all common voting rules including a class of scoring rules which includes the plurality, k-approval, k-veto, veto, and Borda voting rules, maximin, Copeland α for every α ∈ [0,1], and simplified Bucklin voting rules. Hence, in this work, we discover a fundamental vulnerability in using minimax regret based approach in partial preferential setting and propose a novel way to tackle it.

In this paper, we study a maximum likelihood estimation (MLE) approach to voting when the set of alternatives has a multi-issue structure, and the voters' preferences are represented by CP-nets.We first consider general multi-issue domains, and study whether and how issue-by-issue voting rules and sequential voting rules can be represented by MLEs. We first show that issue-by-issue voting rules in which each local rule is itself an MLE (resp. a candidate scoring rule) can be represented by MLEs with a weak (resp. strong) decomposability property. Then, we prove two theorems that state that if the noise model satisfies a very weak decomposability property, then no sequential voting rule that satisfies unanimity can be represented by an MLE, unless the number of voters is bounded.We then consider multi-issue domains in which each issue is binary; for these, we propose a general family of distance-based noise models, of which give an axiomatic characterization. We then propose a more specific family of natural distance-based noise models that are parameterized by a threshold. We identify the complexity of winner determination for the corresponding MLE voting rule in the two most important subcases of this framework.

This paper shows experimentally that hearing expert opinions can be a double-edged sword for collective decision making. We present a majoritarian voting game of common interest where committee members receive not only private information, but also expert information that is more accurate than private information and observed by all members. In theory, there are Bayesian Nash equilibria where the committee members' voting strategy incorporates both types of information and access to expert information enhances the efficiency of the majority decision. However, in the laboratory, expert information had excessive influence on the voting behaviour and prevented efficient aggregation of individual information. We find a large efficiency loss due to the presence of expert information especially when the committee size is large. Using an incentivized questionnaire, we find that many subjects severely underestimate the efficiency gain from information aggregation and they follow expert information much more frequently than efficiency requires. This suggests that those who understand the efficiency gain from information aggregation and perceive the game correctly might nonetheless be “stuck” in an inefficient outcome.

When the first author was a graduate student, some of his professors would argue about the five most influential works in formal political theory. Their lists included classics that affected a wide audience, not just works that were technically advanced. Kenneth Arrow’s Social Choice and Individual Values, Mancur Olson’s Logic of Collective Action, and Anthony Downs’ An Economic Theory of Democracy frequently made the list. Others were discussed, but Buchanan and Tullock’s The Calculus of Consent always seemed to be in the top five.KeywordsMajority RuleExternal CostWinning CoalitionPareto ImprovementUnanimity RuleThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Robustness among multiwinner voting rules

Predictions concerning voting outcomes in crisp spatial models rely heavily on the existence of a core, in the absence of which political players choosing among a set of alternatives by majority rule will not be able to arrive at a stable choice. No matter which option they might initially choose, most voting rules will permit another option to defeat the previously chosen one. Such problems particularly plague majority rule spatial models at dimensionalities greater than one. In a series of recent papers, we have argued that fuzzy spatial models offer a partial solution to this problem. In this paper, we explore the existence of a fuzzy core. Our major conclusion is that a fuzzy core is more likely in two or more dimensions as the number of players increases.

Introduction: Redirecting low acuity patients from emergency departments to primary care walk-in clinics has been identified as a priority by many health authorities. Promoting family physicians for the management of ambulatory patients with urgent health concerns reflects the assumption that primary care facilities can offer high-quality and more affordable ambulatory emergency care. However, no performance assessment framework has been developed for ambulatory emergency care and consequently, quality of care provided in these alternate settings has never been formally compared. Primary objective: To identify structure, process and outcome indicators for ambulatory emergency care. Methods: We will identify and develop quality indicators (QIs) for ambulatory emergency care using a RAND/UCLA Appropriateness Method (RAM) composed of three different steps. First, we will perform a scoping literature review to inventory 1) all previously recommended QIs assessing care provided to ambulatory emergency patients in the ED or the primary care settings; 2) all conditions evaluated with the retrieved QIs; and 3) all outcomes measured by the same QIs. Second, a steering committee composed of the research team and of international experts in performance assessment in emergency and primary care will be presented with the lists of QI-related conditions and outcomes. They will be asked to identify potential outcome indicators for ambulatory emergency care by generating any relevant combinations of one condition and one outcome (e.g. acute asthma exacerbation/re-consultation). Committee members will be given the latitude to use and pair any conditions or outcomes not included in the lists as long as they think the resulting indicators are compatible with the study objectives. Using a structured nominal group approach, they will combine their suggestions and refine the list of potential QIs. This list of potential outcome indicators composed of pairs “condition/outcome” will be merged with the list of already published QIs identified during the literature review. Third, as per the RAM standards, we will assemble an international multidisciplinary panel (n=20) of patients, emergency and primary care providers, researchers and decision makers, after recommendations from international emergency and primary care associations, and from the Canadian Strategy for Patient-Oriented Research (SPOR) Support Units. Through iterative rounds of ratings using both web-based survey tools and videoconferencing, panelists will independently assess all candidate QIs. They will be asked to rate on a nine-level scale to what extent each QI is a relevant and useful measure of ambulatory emergency care quality. From one round to the next, QIs with a median panelist rating score of one to three will be excluded. Those with a median score of seven or more will be automatically included in the final list. QIs with median score of four to six will be retained for future deliberations among the panelists. Rounds of ratings will be conducted until all QIs are classified. Impact: The QIs identified will be used to develop a performance assessment framework for ambulatory emergency care. This will represent an essential step toward testing the assumption that EDs and primary care walk-in clinics provide equivalent care quality to low acuity patients.

public choice theory to familiarize themselves with the masterworks in political theory. [6, 99-101] With this call for broader scholarship in mind, we were impressed in a recent reading of Aristotle's Politics with two aspects of his thought that, in our opinion, should be brought to the attention of modern scholars. First, we examine Aristotle's commentary on voting rules and propose a resolution of an important conflict in the literature interpreting his position on majority rule. Second, we examine Aristotle's general, but not unqualified, belief, presented mainly in analogies, that the collective wisdom of a people was superior to that of the lawgiver's. The main question that we address is whether this superior wisdom was to be embodied in the degree of restrictiveness in the voting rule or in the limits of suffrage. We show that under the former interpretation Aristotle hypothesized an important link between the restrictiveness of the voting rule and the amount of information that is brought to bear in making collective decisions. This is a link perhaps overlooked by modern writers on public choice, and we examine its effect in a model of the optimal voting rule, originally developed by J. M. Buchanan and G. Tullock, to observe its impact on the minimum cost decision rule. [7, 63-84]

In collective decision making, where a voting rule is used to take a\ncollective decision among a group of agents, manipulation by one or more agents\nis usually considered negative behavior to be avoided, or at least to be made\ncomputationally difficult for the agents to perform. However, there are\nscenarios in which a restricted form of manipulation can instead be beneficial.\nIn this paper we consider the iterative version of several voting rules, where\nat each step one agent is allowed to manipulate by modifying his ballot\naccording to a set of restricted manipulation moves which are computationally\neasy and require little information to be performed. We prove convergence of\niterative voting rules when restricted manipulation is allowed, and we present\nexperiments showing that most iterative voting rules have a higher Condorcet\nefficiency than their non-iterative version.\n

We develop a theoretical model of voting behavior in committees when members differ in influence and receive payoffs that condition on the individual vote and the collective decision. Applied to a group decision involving moral costs, the model predicts that the distribution of decision-making power affects committee members’ incentives to make immoral choices: More influential agents tend to support the immoral choice, while less influential agents free-ride. A skewed power distribution makes immoral collective choices more likely. We then present results of a laboratory experiment that studies committee members’ voting behavior and collective choices under different distributions of decision-making power. As hypothesized, we find that the frequency of immoral decisions is positively related to an agent’s voting power.

We study the effect on the participation rate of employing different voting rules in the context of the problem to allocate a fixed monetary budget to two different public projects. Specifically, we compare the mean rule according to which the average of the individually proposed allocations is implemented with the median rule which chooses the allocation proposed by the median voter as the social outcome. We report the results of a field experiment in which subjects (students of KIT) could allocate money to fund two different public projects, the student’s bike shop and a campus garden project. The treatment variable was the collective decision rule employed. While the mean and median rules have very different properties in theory, we found no significant treatment effect on the participation rate. Our results nevertheless shed important light on the use of different voting rules in the context of budget allocation in practice.

Consistent representative democracy

Dynamic bargaining and stability with veto players

Given a large population, it is an intensive task to gather individual preferences over a set of alternatives and arrive at an aggregate or collective preference of the population. We show that social network underlying the population can be harnessed to accomplish this task effectively, by sampling preferences of a small subset of representative nodes. We first develop a Facebook app to create a dataset consisting of preferences of nodes and the underlying social network, using which, we develop models that capture how preferences are distributed among nodes in a typical social network. We hence propose an appropriate objective function for the problem of selecting best representative nodes. We devise two algorithms, namely, Greedy-min which provides a performance guarantee for a wide class of popular voting rules, and Greedy-sum which exhibits excellent performance in practice. We compare the performance of these proposed algorithms against random-polling and popular centrality measures, and provide a detailed analysis of the obtained results. Our analysis suggests that selecting representatives using social network information is advantageous for aggregating preferences related to personal topics (e.g., lifestyle), while random polling with a reasonable sample size is good enough for aggregating preferences related to social topics (e.g., government policies).

This chapter aims to propose a scientific and mathematical-based multiple objective and subjective criteria evaluation technique (MOSCET) to aid decision makers of industrial organization for the most appropriate decision, based on objective and subjective criteria, in those circumstances where human brain is incapable to find the right solution. The algorithm commences with the formation of a homogeneous decision making committee consisting of experts from different sections of the organization. The committee members unanimously choose required important criteria of both subjective and objective category with their depth knowledge and experience. A set of alternatives is primarily chosen through screening test of the alternatives based on sum minimum cut off value of the criteria. Performance ratings in terms of crisp number and linguistic variable are estimated. Fuzzy weighs of the criteria are evaluated with the experts’ perception. Conversion of linguistic variables into crisp number, normalization of performance rating, and integration of rating of alternative with estimated weights of criteria are accomplished sequentially. A unique performance index via performance score for each alternative is computed with proposed exponential technique. The proposed MCDM technique MOSCET is demonstrated through a suitable material handling system selection problem and validated by existing method. The result shows that the proposed method is applicable and useful for decision-making process, considering both objective and subjective criteria under MCDM (Multi Criteria Decision Making).