Abstract:The chapter surveys the recent and fast‐growing literature on the aggregation of logically interrelated propositions, following List and Pettit's formalization of the “doctrinal paradox”. The classical preference aggregation problem is a special case in which propositions take the form of binary preference judgments (“alternative x is better than alternative y”). The first part of the chapter focuses on aggregation methods that satisfy an Arrowian independence condition (“propositionwise aggregation”). In the … Show more
“…Before describing some concrete families of such methods in the next sections, we take a look at a few desirable postulates for aggregation methods. These are inspired by and appropriately modified from postulates studied in the AF case in [3] (which, in turn, have been mostly inspired by postulates from the judgment aggregation literature [11,12]). Free variables in these postulates, e.g., D, v in the first three postulates below, are implicitly universally quantified.…”
“…The question is, can we aggregate these opinions into a single group interpretation that represents the opinion of the group as a whole? In the AF setting, this question (which can be thought of as a special case of the problem of judgment aggregation [11,12]) has been investigated in [3]. There, a general family of methods for aggregating complete AF labellings called interval methods was defined and studied.…”
Abstract. Abstract dialectical frameworks (ADFs) are a knowledge representation formalism introduced as a generalisation of Dung's abstract argumentation frameworks (AFs) by Gerhard Brewka and coauthors. We look at a judgment aggregation problem in ADFs, namely the problem of aggregating a profile of complete interpretations. We generalise the family of interval aggregation methods, studied in the AF case in our previous work, to the ADF case. Along the way we define the notions of down-admissible and up-complete interpretations, that were already previously defined for the AF case by Caminada and Pigozzi. These aggregation methods may open the way to define interesting new semantics for ADFs, such as a generalisation to the ADF case of the ideal semantics for AFs.
“…Before describing some concrete families of such methods in the next sections, we take a look at a few desirable postulates for aggregation methods. These are inspired by and appropriately modified from postulates studied in the AF case in [3] (which, in turn, have been mostly inspired by postulates from the judgment aggregation literature [11,12]). Free variables in these postulates, e.g., D, v in the first three postulates below, are implicitly universally quantified.…”
“…The question is, can we aggregate these opinions into a single group interpretation that represents the opinion of the group as a whole? In the AF setting, this question (which can be thought of as a special case of the problem of judgment aggregation [11,12]) has been investigated in [3]. There, a general family of methods for aggregating complete AF labellings called interval methods was defined and studied.…”
Abstract. Abstract dialectical frameworks (ADFs) are a knowledge representation formalism introduced as a generalisation of Dung's abstract argumentation frameworks (AFs) by Gerhard Brewka and coauthors. We look at a judgment aggregation problem in ADFs, namely the problem of aggregating a profile of complete interpretations. We generalise the family of interval aggregation methods, studied in the AF case in our previous work, to the ADF case. Along the way we define the notions of down-admissible and up-complete interpretations, that were already previously defined for the AF case by Caminada and Pigozzi. These aggregation methods may open the way to define interesting new semantics for ADFs, such as a generalisation to the ADF case of the ideal semantics for AFs.
“…This impossibility result has kicked off the research into questions of judgement aggregation and has led to a flourishing, often technically advanced literature (see List and Puppe, 2009, for a survey). The theorem is important because it systematizes the special case of the discursive dilemma and shows that any form of judgement aggregation over a sufficiently complex agenda fails to meet all the described desiderata together.…”
In recent years, judgement aggregation has emerged as an important area of social choice theory. Judgement aggregation is concerned with aggregating sets of individual judgements over logically connected propositions into a set of collective judgements. It has been shown that even seemingly weak conditions on the aggregation function make it impossible to find functions that produce rational collective judgements from all possible rational individual judgements. This implies that the step from individual judgements to collective judgements requires trade-offs between different desiderata, such as universal domain, rationality, epistemological quality, and unbiasedness. These dilemmas challenge us to decide which conditions we should relax. The typical application for judgement aggregation is the problem of group decision making. Juries and expert committees are the stock examples. However, the relevance of judgement aggregation goes beyond these cases. In this survey I review some core results in the field of judgement aggregation and social epistemology and discuss their implications for the analysis of distributed thinking.
“…Furthermore, the problem of aggregating individual judgments is not restricted to majority voting, but it applies to all aggregation procedures satisfying some seemingly desirable conditions. For an overview, the reader is referred to [13].…”
Abstract. Judgment aggregation is a formal theory reasoning about how a group of agents can aggregate individual judgments on connected propositions into a collective judgment on the same propositions. Three procedures for successfully aggregating judgments sets are: premise-based procedure, conclusion-based procedure and distance-based merging. The conclusion-based procedure has been little investigated because it provides a way to aggregate the conclusions, but not the premises, thus it outputs an incomplete judgment set. The goal of this paper is to present a conclusion-based procedure outputting complete judgment sets.
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