Explaining legal inconsistency

Judges, scholars, and commentators decry inconsistent areas of judicially created policy. This could hurt courts’ policy making efficacy, so why do judges allow it to happen? I show judicially-created policy can become inconsistent when judges explain rules in more abstract terms than they decide cases. To do so, I expand standard case-space models of judicial decision making to account for relationships between specific facts and broader doctrinal dimensions. This model of judicial decision making as a process of multi-step reasoning reveals that preference aggregation in such a context can lead to inconsistent collegial rules. I also outline a class of preference configurations on collegial courts (i.e., multi-member courts) in which this problem cannot arise. These results have implications for several areas of inquiry in judicial politics such as models of principal-agent relationships in judicial hierarchies and empirical research utilizing case facts as predictor variables.

Voter Turnout and Preference Aggregation

We study how voter turnout affects the aggregation of preferences in elections. Under voluntary voting, election outcomes disproportionately aggregate the preferences of voters with low voting cost and high preference intensity. We show identification of the correlation structure among preferences, costs, and perceptions of voting efficacy, and explore how the correlation affects preference aggregation. Using 2004 US presidential election data, we find that young, low-income, less-educated, and minority voters are underrepresented. All of these groups tend to prefer Democrats, except for the less educated. Democrats would have won the majority of the electoral votes if all eligible voters had turned out. (JEL D12, D72)

Reducing the Computational Time for the Kemeny Method by Exploiting Condorcet Properties

Preference aggregation and in particular ranking aggregation are mainly studied by the field of social choice theory but extensively applied in a variety of contexts. Among the most prominent methods for ranking aggregation, the Kemeny method has been proved to be the only one that satisfies some desirable properties such as neutrality, consistency and the Condorcet condition at the same time. Unfortunately, the problem of finding a Kemeny ranking is NP-hard, which prevents practitioners from using it in real-life problems. The state of the art of exact algorithms for the computation of the Kemeny ranking experienced a major boost last year with the presentation of an algorithm that provides searching time guarantee up to 13 alternatives. In this work, we propose an enhanced version of this algorithm based on pruning the search space when some Condorcet properties hold. This enhanced version greatly improves the performance in terms of runtime consumption.

Artificial Intelligence Techniques for Conflict Resolution

Conflict resolution is essential to obtain cooperation in many scenarios such as politics and business, as well as our day to day life. The importance of conflict resolution has driven research in many fields like anthropology, social science, psychology, mathematics, biology and, more recently, in artificial intelligence. Computer science and artificial intelligence have, in turn, been inspired by theories and techniques from these disciplines, which has led to a variety of computational models and approaches, such as automated negotiation, group decision making, argumentation, preference aggregation, and human-machine interaction. To bring together the different research strands and disciplines in conflict resolution, the Workshop on Conflict Resolution in Decision Making (COREDEMA) was organized. This special issue benefited from the workshop series, and consists of significantly extended and revised selected papers from the ECAI 2016 COREDEMA workshop, as well as completely new contributions.

Visualization of preference aggregation based on Weber point in social network group decision-making problem

PurposeThis study aims to construct a Weber point-based model to complete the visualization of preference aggregation in group decision-making problem, in which decision-makers are associated with trust relationship.Design/methodology/approachThis study mainly comprises four parts: trust propagation, preference aggregation, opinion adjustment and alternative selection. Firstly, the incomplete trust between decision-makers is completed with trust transfer operators and propagation probability in trust propagation process. Secondly, a preference aggregation model based on Weber point is proposed to aggregate the group preference visually. Thirdly, opinions are adjusted to reach a consensus. Finally, the ranking of alternatives is determined by the correlation coefficient with the group preference as a reference.FindingsThe Weber point-based model proposed in this study can minimize the gap in the preference of alternatives between the group and all decision-makers, and realize the visualization of aggregation result. A case of plan selection is introduced to illustrate the feasibility and effectiveness of the proposed model.Originality/valueBy comparing the result with the weighted average-based preference aggregation method, the Weber point-based model proposed in this study can show the result of preference aggregation intuitively and improve group consensus.