An algorithm for active learning of lexicographic preferences

Fabien Delecroix (1, 2) , Maxime Morge (1, 2, 3, 4) , Jean-Christophe Routier (1, 2)

1 LIFL - Laboratoire d'Informatique Fondamentale de Lille
2 SMAC - Systèmes Multi-Agents et Comportements
3 Dipartimento di Informatica [Pisa]
4 DI - Dipartimento di Informatica [Pisa]

At the crossroad of preference learning and multicriteria decision aiding, recent researchs on preference elicitation provide useful methods for recommendation systems. In this paper, we consider (partial) lexicographic preferences. In this way, we can consider dilemmas and we show that these situations have a minor impact in practical cases. Based on this observation, we propose an algorithm for active learning of preferences. This algorithm solve the dilemmas by suggesting concrete alternatives which must be ranked by the user.

Domains: Multiagent Systems [cs.MA]; Computer Science and Game Theory [cs.GT]; Computational Engineering, Finance, and Science [cs.CE]; Artificial Intelligence [cs.AI]; Logic in Computer Science [cs.LO]; General Finance [q-fin.GN]

Fabien Delecroix, Maxime Morge, Jean-Christophe Routier. An algorithm for active learning of lexicographic preferences. DA2PL 2012 -- Mons (Belgium) -- November 15-16, 2012, 2012, Belgium. pp.115-122. ⟨hal-00826432⟩