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Agent-based ordinal classification for group decision making

Nefla, Ons; Brigui, Imène; Viappiani, Paolo; Raboun, Oussama (2020), 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), 2020-12, Melbourne (en virtuel), Australia

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WI_IATGroup_based_Ordinal.pdf (593.4Kb)
Type
Communication / Conférence
Date
2020
Conference title
The 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT'20)
Conference date
2020-12
Conference city
Melbourne (en virtuel)
Conference country
Australia
Metadata
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Author(s)
Nefla, Ons
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Brigui, Imène
Viappiani, Paolo
Raboun, Oussama
Abstract (EN)
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.
Subjects / Keywords
simulations; preferences; group decision making; multiagent systems; negotiation; ordinal classification

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