• Voting rules from random relations 

  Wilson, Nic (IOS Press, 2020-08)

  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 define different notions of support, such as whether an ...
• Generating voting rules from random relations 

  Wilson, Nic (International Foundation for Autonomous Agents and MultiAgent Systems (IFAAMAS)., 2019-05)

  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 ...
• Scaling-invariant maximum margin preference learning 

  Montazery, Mojtaba; Wilson, Nic (Elsevier, 2020-10-19)

  One natural way to express preferences over items is to represent them in the form of pairwise comparisons, from which a model is learned in order to predict further preferences. In this setting, if an item a is preferred ...
• Preference inference based on hierarchical and simple lexicographic models 

  Wilson, Nic; George, Anne-Marie; O'Sullivan, Barry (College Publications, 2017)

  Preference Inference involves inferring additional user preferences from elicited or observed preferences, based on assumptions regarding the form of the user’s preference relation. In this paper we consider a situation ...
• Efficient inference and computation of optimal alternatives for preference languages based on lexicographic models 

  Wilson, Nic; George, Anne-Marie (International Joint Conferences on Artificial Intelligence, 2017-08)

  We analyse preference inference, through consistency, for general preference languages based on lexicographic models. We identify a property, which we call strong compositionality , that applies for many natural kinds of ...

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