scholarly journals Computational Social Choice: The First Ten Years and Beyond

2019 ◽  
pp. 48-65 ◽  
Author(s):  
Haris Aziz ◽  
Felix Brandt ◽  
Edith Elkind ◽  
Piotr Skowron
Keyword(s):  
Social Choice ◽  
Computational Social Choice

Parameterization in Computational Social Choice

2015 ◽  
pp. 1-5
Author(s):  
Piotr Faliszewski ◽  
Rolf Niedermeier
Keyword(s):  
Social Choice ◽  
Computational Social Choice

scholarly journals Computational Social Choice Meets Databases

2018 ◽  
Author(s):  
Benny Kimelfeld ◽  
Phokion G. Kolaitis ◽  
Julia Stoyanovich
Keyword(s):  
Computational Complexity ◽  
Social Choice ◽  
Relational Database ◽  
Database Management ◽  
Plurality Rule ◽  
Technical Level ◽  
Computational Social Choice ◽  
Conceptual Level ◽  
Voting Rules ◽  
Conjunctive Queries

We develop a novel framework that aims to create bridges between the computational social choice and the database management communities. This framework enriches the tasks currently supported in computational social choice with relational database context, thus making it possible to formulate sophisticated queries about voting rules, candidates, voters, issues, and positions. At the conceptual level, we give rigorous semantics to queries in this framework by introducing the notions of necessary answers and possible answers to queries. At the technical level, we embark on an investigation of the computational complexity of the necessary answers. In particular, we establish a number of results about the complexity of the necessary answers of conjunctive queries involving the plurality rule that contrast sharply with earlier results about the complexity of the necessary winners under the plurality rule.

scholarly journals A Decision Support Tool for Agricultural Applications Based on Computational Social Choice and Argumentation

2018 ◽  
Vol 9 (3) ◽  
pp. 54-73 ◽  
Author(s):  
Nikos Karanikolas ◽  
Pierre Bisquert ◽  
Patrice Buche ◽  
Christos Kaklamanis ◽  
Rallou Thomopoulos
Keyword(s):  
Decision Making ◽  
Social Choice ◽  
Food Packaging ◽  
Software Tool ◽  
Decision Support Tool ◽  
Decision Problems ◽  
Computational Social Choice ◽  
Support Tool ◽  
The Social ◽  
Agricultural Applications

In the current article, the authors describe an applied procedure to support collective decision making for applications in agriculture. An extended 2-page abstract of this paper has been accepted by the EFITA WCCA congress and this manuscript is an extended version of this submission. The problem the authors are facing in this paper is how to reach the best decision regarding issues coming from agricultural engineering with the aid of Computational Social Choice (CSC) and Argumentation Framework (AF). In the literature of decision-making, several approaches from the domains of CSC and AF have been used autonomously to support decisions. It is our belief that with the combination of these two fields the authors can propose socially fair decisions which take into account both (1) the involved agents' preferences and (2) the justifications behind these preferences. Therefore, this article implements a software tool for decision-making which is composed of two main systems, i.e., the social choice system and the deliberation system. In this article, the authors describe thoroughly the social choice system of our tool and how it can be applied to different alternatives on the valorization of materials coming from agriculture. As an example, that is demonstrated an application of our tool in the context of Ecobiocap European project where several decision problems are to be addressed. These decision problems consist in finding the best solutions for questions regarding food packaging and end-of-life management.

Developing the aggregate empirical side of computational social choice

2013 ◽  
Vol 68 (1-3) ◽  
pp. 31-64 ◽  
Author(s):  
T. Nicolaus Tideman ◽  
Florenz Plassmann
Keyword(s):  
Social Choice ◽  
Computational Social Choice

scholarly journals The 1st international workshop on computational social choice

2008 ◽  
Vol 23 (2) ◽  
pp. 213-215 ◽  
Author(s):  
ULLE ENDRISS
Keyword(s):  
Artificial Intelligence ◽  
Social Choice ◽  
Computer Science ◽  
Multiagent Systems ◽  
Choice Theory ◽  
International Workshop ◽  
Social Choice Theory ◽  
Computational Techniques ◽  
Computational Social Choice ◽  
Computer Scientists

AbsractComputational social choice is a new discipline currently emerging at the interface of social choice theory and computer science. It is concerned with the application of computational techniques to the study of social choice mechanisms, and with the integration of social choice paradigms into computing. The first international workshop specifically dedicated to this topic took place in December 2006 in Amsterdam, attracting a mix of computer scientists, people working in artificial intelligence and multiagent systems, economists, game and social choice theorists, logicians, mathematicians, philosophers, and psychologists as participants.

scholarly journals A Structural Approach to Activity Selection

2018 ◽  
Author(s):  
Eduard Eiben ◽  
Robert Ganian ◽  
Sebastian Ordyniak
Keyword(s):  
Social Choice ◽  
Parameterized Complexity ◽  
Group Activity ◽  
Structural Approach ◽  
Selection Problem ◽  
Computational Social Choice ◽  
Agent Interactions ◽  
Choice Group

The general task of finding an assignment of agents to activities under certain stability and rationality constraints has led to the introduction of two prominent problems in the area of computational social choice: Group Activity Selection (GASP) and Stable Invitations (SIP). Here we introduce and study the Comprehensive Activity Selection Problem, which naturally generalizes both of these problems. In particular, we apply the parameterized complexity paradigm, which has already been successfully employed for SIP and GASP. While previous work has focused strongly on parameters such as solution size or number of activities, here we focus on parameters which capture the complexity of agent-to-agent interactions. Our results include a comprehensive complexity map for CAS under various restrictions on the number of activities in combination with restrictions on the complexity of agent interactions.

scholarly journals Protecting Elections by Recounting Ballots

2019 ◽  
Author(s):  
Edith Elkind ◽  
Jiarui Gan ◽  
Svetlana Obraztsova ◽  
Zinovi Rabinovich ◽  
Alexandros A. Voudouris
Keyword(s):  
Social Choice ◽  
Stackelberg Game ◽  
Election Outcome ◽  
Complete Picture ◽  
Plurality Rule ◽  
Computational Social Choice ◽  
Two Stage

Complexity of voting manipulation is a prominent topic in computational social choice. In this work, we consider a two-stage voting manipulation scenario. First, a malicious party (an attacker) attempts to manipulate the election outcome in favor of a preferred candidate by changing the vote counts in some of the voting districts. Afterwards, another party (a defender), which cares about the voters' wishes, demands a recount in a subset of the manipulated districts, restoring their vote counts to their original values. We investigate the resulting Stackelberg game for the case where votes are aggregated using two variants of the Plurality rule, and obtain an almost complete picture of the complexity landscape, both from the attacker's and from the defender's perspective.

scholarly journals Election with Bribe-Effect Uncertainty: A Dichotomy Result

2019 ◽  
Author(s):  
Lin Chen ◽  
Lei Xu ◽  
Shouhuai Xu ◽  
Zhimin Gao ◽  
Weidong Shi
Keyword(s):  
Computational Complexity ◽  
Social Choice ◽  
Deterministic Model ◽  
Threshold Value ◽  
Realistic Model ◽  
Computational Social Choice ◽  
Mathematical Property ◽  
New Model ◽  
Fixed Threshold

We consider the electoral bribery problem in computational social choice. In this context, extensive studies have been carried out to analyze the computational vulnerability of various voting (or election) rules. However, essentially all prior studies assume a deterministic model where each voter has an associated threshold value, which is used as follows. A voter will take a bribe and vote according to the attacker's (i.e., briber's) preference when the amount of the bribe is above the threshold, and a voter will not take a bribe when the amount of the bribe is not above the threshold (in this case, the voter will vote according to its own preference, rather than the attacker's). In this paper, we initiate the study of a more realistic model where each voter is associated with a  willingness function, rather than a fixed threshold value. The willingness function characterizes the  likelihood a bribed voter would vote according to the attacker's preference; we call this bribe-effect uncertainty. We characterize the computational complexity of the electoral bribery problem in this new model. In particular, we discover a dichotomy result: a certain mathematical property of the willingness function dictates whether or not the computational hardness can serve as a deterrence to bribery attackers.

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