Negotiating Socially Optimal Allocations of Resources

Endriss, Ulle; Maudet, Nicolas; Fariba, Sadri; Francesca, Toni

Endriss, Ulle; Maudet, Nicolas; Fariba, Sadri; Francesca, Toni (2006), Negotiating Socially Optimal Allocations of Resources, The Journal of Artificial Intelligence Research, 25, 3, p. 315–348. http://dx.doi.org/doi:10.1613/jair.1870

Type

Article accepté pour publication ou publié

Date

2006

Nom de la revue

The Journal of Artificial Intelligence Research

Volume

Numéro

Éditeur

AI Access Foundation

Pages

315–348

Résumé (EN)

A multiagent system may be thought of as an artificial society of autonomous software agents and we can apply concepts borrowed from welfare economics and social choice theory to assess the social welfare of such an agent society. In this paper, we study an abstract negotiation framework where agents can agree on multilateral deals to exchange bundles of indivisible resources. We then analyse how these deals affect social welfare for different instances of the basic framework and different interpretations of the concept of social welfare itself. In particular, we show how certain classes of deals are both sufficient and necessary to guarantee that a socially optimal allocation of resources will be reached eventually.