Condorcet's paradox

Gehrlein, William V.

doi:10.1007/bf00143070

Cited by 176 publications

(69 citation statements)

References 81 publications

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“…However, existing approaches to annotation noise are primarily based on majority voting which requires a costly volume of redundant annotations. Moreover, as a local (per-pair) inconsistency filtering method, it has no effect on global inconsistency and even risks introducing additional inconsistency due to the well-known Condorcet's paradox [15].…”

Section: Related Workmentioning

confidence: 99%

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Interestingness Prediction by Robust Learning to Rank

Hospedales

Xiang

et al. 2014

Lecture Notes in Computer Science

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Abstract. The problem of predicting image or video interestingness from their low-level feature representations has received increasing interest. As a highly subjective visual attribute, annotating the interestingness value of training data for learning a prediction model is challenging. To make the annotation less subjective and more reliable, recent studies employ crowdsourcing tools to collect pairwise comparisons -relying on majority voting to prune the annotation outliers/errors. In this paper, we propose a more principled way to identify annotation outliers by formulating the interestingness prediction task as a unified robust learning to rank problem, tackling both the outlier detection and interestingness prediction tasks jointly. Extensive experiments on both image and video interestingness benchmark datasets demonstrate that our new approach significantly outperforms state-of-the-art alternatives.

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Section: Related Workmentioning

confidence: 99%

“…This makes our model detect E → A as an outlier, contrary to the majority voting decision. In particular, the majority voting will introduce a loop comparison A < B < C < D < E < A which is the well-known Condorcet's paradox [15]. We further give two more extreme cases in Fig.…”

Section: Framework Formulationmentioning

confidence: 99%

Interestingness Prediction by Robust Learning to Rank

Hospedales

Xiang

et al. 2014

Lecture Notes in Computer Science

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“…A more general form lies in the possibility that pairwise majority voting may generate irrational -specifically, cyclical and thereby intransitive -collective preference orderings, such as xPy, yPz, and zPx. 5 (On the various forms of the paradox, see Gehrlein 1983. )…”

Section: Profilementioning

confidence: 99%

Deliberation, Single-Peakedness, and the Possibility of Meaningful Democracy: Evidence from Deliberative Polls

List

Luskin

Fishkin

et al. 2013

The Journal of Politics

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“…When majority preferences are cyclical, majority voting yields no stable winner-a phenomenon known as 'Condorcet's paradox' (e.g. Gehrlein 1983). Moreover, this problem is not restricted to majority voting.…”

Section: Basic Definitionsmentioning

confidence: 99%

Group decisions in humans and animals: a survey

Conradt

List

2008

Phil. Trans. R. Soc. B

280

198

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Humans routinely make many decisions collectively, whether they choose a restaurant with friends, elect political leaders or decide actions to tackle international problems, such as climate change, that affect the future of the whole planet. We might be less aware of it, but group decisions are just as important to social animals as they are for us. Animal groups have to collectively decide about communal movements, activities, nesting sites and enterprises, such as cooperative breeding or hunting, that crucially affect their survival and reproduction. While human group decisions have been studied for millennia, the study of animal group decisions is relatively young, but is now expanding rapidly. It emerges that group decisions in animals pose many similar questions to those in humans. The purpose of the present issue is to integrate and combine approaches in the social and natural sciences in an area in which theoretical challenges and research questions are often similar, and to introduce each discipline to the other's key ideas, findings and successful methods. In order to make such an introduction as effective as possible, here, we briefly review conceptual similarities and differences between the sciences, and provide a guide to the present issue.Keywords: collective decisions; communal decisions; conflict resolution; cooperation; information sharing; social behaviour GENERAL BACKGROUNDHumans usually live in highly sophisticated societies. This implies that many important decisions are made not by individuals acting alone, but by groups of individuals acting collectively. Group decisions in humans range from small-scale decisions, such as those taken by groups of relatives, friends or colleagues, to large-scale decisions, such as nation-wide democratic elections and international agreements. Clearly, human societies cannot function without group decisions, and some of the most pressing problems facing humanity result from failures to reach a group consensus (e.g. the signing of the Kyoto treaty on controlling greenhouse gas emissions). Group decision making has been a central topic in all of the social sciences for millennia (e.g. Plato: The Republic 360 BC). Nevertheless, many questions remain open, particularly how conflicting interests and the sharing of dispersed information are actually, and should be, in principle, reconciled so as to facilitate cooperation and to reach outcomes that meet various optimality criteria. These are some of the fundamental questions of social choice theory (e.g. Arrow 1951Arrow /1963Austen-Smith & Banks 1999Sen 1999;Dryzek & List 2003). A large number of animal species also live in groups (Krause & Ruxton 2002), some of which can be very complex (e.g. eusocial bees, wasps, ants, termites and mole rats). Group decision making is just as important for social animals as it is for us (see Conradt & Roper 2005 for a review). Dispersing swarms of bees and ants collectively choose new nest sites on which their survival depends (Seeley & Buhrman 1999;Visscher 2007;Visscher & Seele...

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Condorcet's paradox

Cited by 176 publications

References 81 publications

Interestingness Prediction by Robust Learning to Rank

Interestingness Prediction by Robust Learning to Rank

Deliberation, Single-Peakedness, and the Possibility of Meaningful Democracy: Evidence from Deliberative Polls

Group decisions in humans and animals: a survey

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