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Agent-based ordinal classification for group decision making

Paolo Viappiani
Oussama Raboun
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In this article we are interested in group decision aiding for an ordinal classification problem. Our approach is based on a multiagent system where each decision maker is represented by a user agent and the process is guided by a mediator agent. Each user agent has a personalized preferencebased behavior defined by a utility function. The aim of the process is to converge to a group classification using a negotiation procedure. We present an experiment with real and simulated data in order to illustrate our approach and assess its performance (with respect to both user satisfaction and privacy) comparing it with two centralized methods.
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hal-03037304 , version 1 (03-12-2020)


  • HAL Id : hal-03037304 , version 1


Ons Nefla, Imène Brigui, Paolo Viappiani, Oussama Raboun. Agent-based ordinal classification for group decision making. The 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT'20), Dec 2020, Melbourne (en virtuel), Australia. ⟨hal-03037304⟩
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