MoL-2017-04: Covertly Controlling Choices: Manipulating Decision Making Under Partial Knowledge

MoL-2017-04: Griffioen, Simone (2017) Covertly Controlling Choices: Manipulating Decision Making Under Partial Knowledge. [Report]

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The problem of reaching collective decisions on interconnected issues is studied in binary judgement aggregation with integrity constraints. In this thesis, we present an implementation of the framework for binary judgement aggregation and extend this implementation to study the decision making process. First we introduce several (new) rules, such as the priority rule, the distance based rule and the least squares rule. We illustrate and motivate the usefulness of these rules by examples using the implementation. We introduce the notion of a majority preserving rule and we prove that both the priority and the distance based rule are majority preserving. It is well known that most reasonable aggregation rules are susceptible to manipulation under full knowledge. We study manipulation of the decision making process. To generalize this, we quantify the preferences of agents and we use this to study manipulations under both full, but also partial knowledge. We illustrate how agents could manipulate certain aggregation rules. Not only aggregation rules can be manipulated, other parts of the decision making process are susceptible to manipulation as well. An agent could use her knowledge for making a choice of an aggregation rule or when setting an agenda. We adapt a known concept of agenda manipulation to our setting and combine this with manipulation of the aggregation rule. We investigate how much knowledge agents need to be able to manipulate and we show that even without knowledge, there are plenty of opportunities for manipulation. Finally, we use the quantified preferences to quantify manipulability of aggregation rules under different amounts of knowledge, and we show how we can use this quantification to choose a rule that is less manipulable.

Item Type: Report
Report Nr: MoL-2017-04
Series Name: Master of Logic Thesis (MoL) Series
Year: 2017
Subjects: Logic
Depositing User: Dr Marco Vervoort
Date Deposited: 22 Jun 2017 15:37
Last Modified: 13 Jul 2017 13:27

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