3rd ILLC Workshop on Collective Decision Making

The Institute for Logic, Language and Computation (ILLC) at the University of Amsterdam will host the 3rd ILLC Workshop on Collective Decision Making on 6-7 June 2019 in the historic centre of Amsterdam.

The scientific programme of this informal workshop will be structured around a number of invited talks on topics broadly related to the design and analysis of mechanisms for collective decision making. There will be an open poster session, one of those infamous rump sessions so beloved by the computational social choice research community, and plenty of time for discussion. Previous editions took place in 2013 and 2015. See also the Call for Posters and Participation.

Invited talks will be delivered by Antoinette Baujard (Saint-Étienne), Caspar Chorus (Delft), Umberto Grandi (Toulouse), Davide Grossi (Groningen), Ronald de Haan (Amsterdam), Arianna Novaro (Toulouse), Daniele Porello (Trento), Ton Storcken (Maastricht), Zoi Terzopoulou (Amsterdam), Matthijs van Veelen (Amsterdam), and Anaëlle Wilczynski (Munich). The poster session will take place on Thursday afternoon and the rump session (five-minute presentations on anything you like) on Friday afternoon. You can sign up for the latter during the workshop itself.

• Some Annoying Grading Scale Effects under Different Versions of Evaluative Voting (slides)
  Antoinette Baujard (University of Lyon at Saint-Étienne and GATE Lyon Saint-Étienne)

  Abstract: Many voters appreciate more expressive voting rules; e.g., in evaluative voting, longer grading scales and/or negative grades seem desirable as far as, all else being equal, they allow more expressivity. This talk deals with evaluative (or "range") voting, and studies to what extent the behavior of the voters, and the outcome of the election, are sensitive to the grading scale. We use data from an experiment conducted in parallel to the 2017 French presidential election: on the day of the first round, alternative evaluative voting rules were proposed to the voters using different scales. The protocol has been adapted to scrutinize the negative grade effect and the length effect in grading scales. First, our results confirm that the introduction of a negative grade disfavors "exclusive" candidates, but they now more generally establish that it disfavors major candidates and favors minor candidates. Second, under non-negative scales of different lengths, distorsions may concern specific categories of candidates: exclusive candidates may be relatively disfavored with longer scales, especially compared to those attracting only a contingent media coverage and are rather unknown to the voters. Overall, we highlight that the benefit of expressivity provided by a longer scale or negative grades requires a trade-off with the controversial advantage given to uncovered candidates. (This is joint work with Isabelle Lebon, Jean-François Laslier and Herrade Igersheim.)

• Discrete Choice Theory, Choice Experiments and Taboos: Empirical Social Science Meets AI (slides)
  Caspar Chorus (TU Delft)

  Abstract: Discrete choice theory provides a formal, mathematical approach to model human decision making. Developed in the 1970s, choice models are nowadays routinely used in fields as diverse as econometrics, transport, marketing, political science and healthcare. The data used to estimate and validate such models often comes from so-called choice experiments, in which participants are faced with carefully constructed choice sets that allow for a statistically efficient inference of behavioral parameters. After a quick introduction to this field, I will present a choice model that deviates from mainstream models which presume that decision makers are always willing to make trade-offs (e.g., between price and quality of a consumer good). My Taboo-Trade-Off-Aversion model is rooted in moral psychology, and formalizes the notion that in some cases, people find the mere act of making a trade-off morally problematic; think of attaching a monetary value to a human life (which is relevant input for healthcare and traffic safety policies). In a dataset collected by means of a tailor-made choice experiment, I report sizable heterogeneity in the population regarding the presence and size of taboo-trade-off-aversion. In the last part of my talk, I will explain how the outcomes of this empirical modeling effort can be used to construct a meta-normative theory to help AI make decisions in morally sensitive contexts.

• Multi-Issue Opinion Diffusion under Constraints (slides)
  Umberto Grandi (University of Toulouse and IRIT)

  Abstract: Most existing models of opinion diffusion on networks neglect the existence of logical constraints that might correlate individual opinions on multiple issues. In this work we model the diffusion of constrained opinions on a social network as an iterated process of aggregating neighbouring opinions. To overcome the problem of updating towards inconsistent influencing opinions, our model is based on individual updates on subsets of the issues of limited size called propositionwise updates. By adapting notions from the theory of boolean functions, we identify classes of integrity constraints on which propositionwise updates decrease the influence gap between nodes of the network and their influencers caused by the presence of an integrity constraint. Furthermore, we provide a detailed study of the termination of the proposed diffusion processes. (This is joint work with Laurent Perrussel from the University of Toulouse and Sirin Botan from the University of Amsterdam.)

• Blockchain Consensus, Opinion Diffusion and Simple Games (slides)
  Davide Grossi (University of Groningen)

  Abstract: I will present a model of binary opinion diffusion on networks and show how it can be used as an abstraction to analyse a specific type of consensus protocols in blockchains (e.g., protocols used in systems like Ripple and Stellar). At a high level, such protocols work through a form of iterated voting run on a network of trustees that is constructed locally in a distributed fashion. The model highlights specific weaknesses of those protocols and suggests the application of methods from (computational) social choice to problems and protocols from distributed computing.

• General Yet Computationally Efficient Aggregation Frameworks (slides)
  Ronald de Haan (University of Amsterdam)

  Abstract: Several settings in computational social choice concern the aggregation of individual opinions into a single collective opinion. Examples include (committee) elections and voting on which projects to fund within a given budget. For many such settings, efficient algorithms for various aggregation rules have been found. However, these algorithms typically cannot deal with additional constraints (e.g., diversity constraints for committees, or dependencies between projects), whereas such additional constraints are often important when using the aggregation rules in practice. I propose to develop general frameworks that can be used to model different aggregation settings, including various additional constraints that can come up in applications. When developing such a general framework, there is a tradeoff between generality and computational tractability. The social choice model of judgment aggregation can be used as such a general aggregation framework. I will discuss several results that strike a balance between generality and tractability, and explain how these results are relevant for specific aggregation applications.

• Strategic Majoritarian Voting with Propositional Goals (slides)
  Arianna Novaro (University of Toulouse and IRIT)

  Abstract: In this talk I will introduce the framework of goal-based voting, where a group of agents has to take a collective decision over some binary issues and each individual is motivated by a goal expressed as a formula of propositional logic. The collective decision is given by a function, whose input are the individual goals, and I will focus on three variants of majority. Agents holding individual goals naturally lead to situations where strategic voting may occur: i.e., when an agent reporting an untruthful goal may get a better outcome. I will present manipulability results for the general case, as well as strategy-proofness results when the language of the goals is restricted or the agents can only use a subset of strategic actions. Finally, I will talk about how computationally hard is it for an agent to know if they can profitably manipulate.

• Reason-Based Preferences and Preference Aggregation (slides)
  Daniele Porello (Laboratory for Applied Ontology, ISTC-CNR, Trento)

  Abstract: In this talk, I will explore the modelling of reason-based preferences introduced by Dietrich and List. In this setting, individual preferences are motivated by the properties of the options involved: i.e., an agent prefers x to y iff the reasons for x outweigh the reasons for y. I will propose a method for enabling agents to express weighted combinations of reasons for justifying their preferences. To this end, I will introduce weighted description logics to reason about combinations of salient properties. Moreover, I will discuss a number of strategies for aggregating individual preferences by leveraging on the information provided by the reasons.

• Collective Choice Rules on Domains with A Priori Information
  Ton Storcken (Maastricht University)

  Abstract: In this restricted-domain approach it is assumed that parts of the agents' preferences are known a priori. This means that the admissible preferences of an agent contain a given partial order, where this partial order may differ per agent. It appears that these sets of admissible preferences are convex with respect to the betweenness relation induced by the Kemeny distance on preferences. Necessary and sufficient conditions are formulated under which such restricted domains admit unanimous, strategy-proof, and non-dictatorial choice rules. Loosely speaking it boils down to admitting monotone and non-image-dictatorial decision rules on two alternatives, where the other alternatives are completely disregarded and these two alternatives are the maximal elements with respect to all a priori given partial orders. (This is joint work with Shashwat Khare.)

• Collective Decision Making with Incomplete Individual Opinions (slides)
  Zoi Terzopoulou (University of Amsterdam)

  Abstract: Across different formal frameworks for collective decision making (e.g., voting, preference and judgment aggregation), a common assumption is that the agents hold and report opinions that are complete, i.e., concern all issues for which a collective decision has to be made. I confront this assumption, arguing that in many reasonable scenarios the agents can be expected (and should be given the freedom) to either have or report incomplete opinions. How can we then modify our models to account for such incompleteness, what challenges do we need to overcome, and what changes may be caused in classical results of the field? In this talk I will open this discussion and provide several theoretical insights motivated by examples of practical interest.

• Good and Evil (slides)
  Matthijs van Veelen (University of Amsterdam)

  Abstract: I will give an overview of the evolutionary explanations of altruism and cooperation. There are three broad categories: population structure, repeated interaction, and partner choice. Population structure implies that individuals do not interact (uniformly) randomly, but one's own type is predictive of the type of the individual one interacts with. There are interesting complications here, such as the cancellation effect. Repeated interaction turns one-shot games into repeated games, with, typically, many more equilibria than the one-shot game, including more cooperative ones. We will see that this allows for transitions into and out of cooperation. With partner choice, a species can become their own selective force. Ingredients from these three broad categories can also interact in interesting ways.

• Local Envy-Freeness in House Allocation Problems (slides)
  Anaëlle Wilczynski (TU Munich)

  Abstract: We study the fair division problem consisting in allocating exactly one item per agent, which is called house allocation, so as to avoid, or minimize, envy. Envy-free allocations are rare and trivial in house allocation: every agent must get her most preferred object. Moreover, assuming that any agent is able to envy any other agent is a strong assumption since the visibility or the jealousy of the agents may be limited due to a lack of knowledge or specific relationships. Consequently we aim to relax the notion of envy in house allocation by considering a notion of local envy which is determined by a network structure over the agents, represented by a directed graph. In this context, an allocation is locally envy-free if no agent envies one of her successors in the graph. The existence of a locally envy-free allocation is investigated, as well as the minimization of local envy in case a locally envy-free allocation does not exist. We study the complexity of these problems and also examine some variants where the role of the central authority is more or less important.

The following posters have been accepted for inclusion into the programme and will be presented on the afternoon of the first day of the workshop:

• Studying Deliberated Judgements
  Olivier Cailloux (Paris-Dauphine University)

• Does Deliberation Improve the Reliability of Epistemic Democracy?
  Huihui Ding and Marcus Pivato (University of Cergy-Pontoise)

• Net Borda Rule with Desirability
  Takashi Kurihara (Waseda University) and Edith Elkind (University of Oxford)

• On Proportional Belief Merging
  Adrian Haret, Martin Lackner, Andreas Pfandler, and Johannes Wallner (TU Wien)

• On Rational Delegations in Liquid Democracy
  Daan Bloembergen (CWI, Amsterdam), Davide Grossi (University of Groningen), and Martin Lackner (TU Wien)

• Multiwinner Approval Voting with a Variable Number of Winners: A Possible Application in the Medical Domain
  Jan Maly, Stefan Woltran, Martin Lackner, and Clemens Gangl (TU Wien)

• An Ordinal Banzhaf Index for Social Ranking
  Hossein Khani, Stefano Moretti, and Meltem Öztürk (Paris-Dauphine University)

• How Hard Is It to Predict the Outcome of an Election?
  Dorothea Baumeister, Tobias Hogrebe, and Daniel Neugebauer (Heinrich Heine University Düsseldorf)

• Liquid Democracy with Ranked Delegations
  Markus Brill, Anne-Marie George, Martin Lackner, and Ulrike Schmidt-Kraepelin (TU Berlin)

• Practical One-to-Many Negotiation Challenges
  Faria Nassiri-Mofakham and Tim Baarslag (CWI, Amsterdam)

• Simultaneous Elicitation of Committee and Voter Preferences
  Beatrice Napolitano (Paris-Dauphine University), Olivier Cailloux (Paris-Dauphine University), and Paolo Viappiani (Sorbonne University)

• The Excess Method: A Multiwinner Approval Voting Procedure to Allocate Wasted Votes
  Steven Brams (New York University), Markus Brill (TU Berlin), and Anne-Marie George (TU Berlin)

• Popularity in Hedonic Games
  Martin Bullinger (TU Munich)

• An Analytical and Experimental Comparison of Maximal Lottery Schemes
  Florian Brandl, Felix Brandt, and Christian Stricker (TU Munich)

Photos by Stéphane Airiau.

We would like to get a realistic estimate of the number of attendees well in advance of the event, so as to be able to order the right amount of coffee. Here is how we hope to achieve this:

Early registration was free and possible using this form until Saturday, 25 May 2019.

Late registration costs € 10, to be paid in cash on site.

The first five registered participants will be offered a free copy of the book Trends in Computational Social Choice.

De Doelenzaal, University Library, Singel 425, Amsterdam

Trams 2, 11, and 12 stop at Koningsplein across the street. Metro 52 stops at Rokin, a 5-minute walk away. The main train station (Amsterdam Centraal) is a 20-minute walk away.

This workshop is organised by Ulle Endriss, with the help of Suzanne Bloks, Arthur Boixel, and Sirin Botan. Please feel free to contact anyone of us if there is something we can help you with.