Dear all,

This week we are going to have two talks in the Computational Social Choice Seminar at the ILLC, both of them related to judgment aggregation, but deviating from the standard model in different ways. On Thursday at 15:00 Marija Slavkovik (Bergen) will speak about aggregating likelihood judgments, and on Friday at 16:00 Arianna Novaro (Toulouse) will speak about goal-based voting. I include both abstracts below.

As always, for more information on the COMSOC Seminar, please consult https://staff.science.uva.nl/u.endriss/seminar/.

All the best, Ulle

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Speaker: Marija Slavkovik (Bergen) Title: Aggregation of Likelihood Judgments Date: Thursday 28 February 2019 Time: 15:00 Location: Room F1.15, Science Park 107, The Netherlands

Abstract: Judgment aggregation studies methods for aggregating individual opinions on logically related issues. So far, concrete aggregators have been proposed only for aggregating binary, or Boolean, judgments. However, opinion sources do not always provide binary judgments. Sometimes we have judgments expressing likelihood, not certainty, of whether a proposition is true. We here propose a framework and a first set of specific aggregation methods for aggregating likelihood judgments. Our aggregation methods are mainly obtained by generalizing known classic judgment aggregation methods that satisfy some essential desirable properties.

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Speaker: Arianna Novaro (Toulouse) Title: Collective Decisions with Logic-based Goals Date: Friday 1 March 2019 Time: 16:00 Location: Room F1.15, Science Park 107, Amsterdam

Abstract: In this talk I will present the framework of goal-based voting, where agents express their individual goals as formulas of propositional logic, with the common objective of reaching a collective decision (e.g., which points of interest to visit together when exploring a new city). I will present some voting rules for this setting, adapted from the literature on Social Choice Theory, which will then be studied from both an axiomatic and a computational perspective. In the final part, I will focus on agents acting strategically, i.e., agents reporting a goal that differs from their truthful one if by doing so they can get a better outcome.