Emergent Diagnosis via Coalition Formation

Carine Webber (1) , Sylvie Pesty (1)

1 Leibniz - IMAG - Laboratoire Leibniz

This paper presents a mechanism of coalition formation where agents solve a problem of diagnosis. Our approach considers that a diagnosis may be seen as the result of an emergent process where findings (at a microscopic level) are interpreted by entities (at a macroscopic level). At the micro-level agents interact and form coalitions. At the macro-level specialized agents are able to interpret coalition formation and infer a diagnosis. Our domain of application is student modelling and in this framework we conceive it as a diagnosis task where a ‘state of conceptions' is ascribed to a student based on his/her prob-lem-solving activities.

Mots clés: Multiagent systems; Student diagnosis

Domaines: Environnements Informatiques pour l'Apprentissage Humain; Education

Carine Webber, Sylvie Pesty. Emergent Diagnosis via Coalition Formation. Proceedings of the 8th Iberoamerican Conference on Artificial Intelligence, 2002, pp.755-764. ⟨hal-00003044⟩