Generating voting rules from random relations

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Wilson, Nic
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International Foundation for Autonomous Agents and MultiAgent Systems (IFAAMAS).
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We consider a way of generating voting rules based on a random relation, the winners being alternatives that have the highest probability of being supported. We consider different notions of support, such as whether an alternative dominates the other alternatives, or whether an alternative is undominated, and we consider structural assumptions on the form of the random relation, such as being acyclic, asymmetric, connex or transitive. We give sufficient conditions on the supporting function for the associated voting rule to satisfy various properties such as Pareto and monotonicity. The random generation scheme involves a parameter p between zero and one. Further voting rules are obtained by tending p to zero, and by tending p to one, and these limiting rules satisfy a homogeneity property, and, in certain cases, Condorcet consistency. We define a language of supporting functions based on eight natural properties, and categorise the different rules that can be generated for the limiting p cases.
Voting rules , Random relations , Limiting probabilities
Wilson, N. (2019) 'Generating Voting Rules from Random Relations', Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, AAMAS '19, Montreal, Canada, 13-17 May. pp. 2267-2269. isbn: 978-1-4503-6309-9
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