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Generalized scoring rules: a framework that reconciles Borda and Condorcet

Generalized scoring rules: a framework that reconciles Borda and Condorcet Generalized Scoring Rules: A Framework That Reconciles Borda and Condorcet LIRONG XIA Harvard University Generalized scoring rules [Xia and Conitzer 08] are a relatively new class of social choice mechanisms. In this paper, we survey developments in generalized scoring rules, showing that they provide a fruitful framework to obtain general results, and also reconcile the Borda approach and Condorcet approach via a new social choice axiom. We comment on some high-level ideas behind GSRs and their connection to Machine Learning, and point out some ongoing work and future directions. Categories and Subject Descriptors: J.4 [Computer Applications]: Social and Behavioral Sciences--Economics; I.2.11 [Distributed Artificial Intelligence]: Multiagent Systems General Terms: Algorithms, Economics, Theory Additional Key Words and Phrases: Computational social choice, generalized scoring rules 1. INTRODUCTION Social choice theory focuses on developing principles and methods for representation and aggregation of individual ordinal preferences. Perhaps the most well-known application of social choice theory is political elections. Over centuries, many social choice mechanisms have been proposed and analyzed in the context of elections, where each agent (voter) uses a linear order over the alternatives (candidates) to represent her preferences (her vote). For historical reasons, we will use voting rules to denote social http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM SIGecom Exchanges Association for Computing Machinery

Generalized scoring rules: a framework that reconciles Borda and Condorcet

Xia, Lirong
ACM SIGecom Exchanges , Volume 12 (1) – Jun 1, 2013
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Publisher
Association for Computing Machinery
Copyright
Copyright © 2013 by ACM Inc.
ISSN
1551-9031
DOI
10.1145/2509013.2509020
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Abstract

Generalized Scoring Rules: A Framework That Reconciles Borda and Condorcet LIRONG XIA Harvard University Generalized scoring rules [Xia and Conitzer 08] are a relatively new class of social choice mechanisms. In this paper, we survey developments in generalized scoring rules, showing that they provide a fruitful framework to obtain general results, and also reconcile the Borda approach and Condorcet approach via a new social choice axiom. We comment on some high-level ideas behind GSRs and their connection to Machine Learning, and point out some ongoing work and future directions. Categories and Subject Descriptors: J.4 [Computer Applications]: Social and Behavioral Sciences--Economics; I.2.11 [Distributed Artificial Intelligence]: Multiagent Systems General Terms: Algorithms, Economics, Theory Additional Key Words and Phrases: Computational social choice, generalized scoring rules 1. INTRODUCTION Social choice theory focuses on developing principles and methods for representation and aggregation of individual ordinal preferences. Perhaps the most well-known application of social choice theory is political elections. Over centuries, many social choice mechanisms have been proposed and analyzed in the context of elections, where each agent (voter) uses a linear order over the alternatives (candidates) to represent her preferences (her vote). For historical reasons, we will use voting rules to denote social

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ACM SIGecom Exchanges – Association for Computing Machinery

Published: Jun 1, 2013

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