Séminaire IRIT-UT1 - Dongmo Zhang

le 30 juin 2009

Manufacture des Tabacs - ME303

Séminaire IRIT-UT1 - Mardi 30 juin 2009 - 12h45 - Salle ME303


Dongmo Zhang
- University of Western Sydney

"
An AI View of Bargaining Theory"

As one of the most fundamental models in modern economic theory, the Nash bargaining solution (Nash 1950) has been developed in the past six decades into a high sophisticated theory with varieties of models, extensions, and applications.

Despite mathematical simplicity and elegance, it has been found that such a purely numerical theory of bargaining is difficult to model bargaining among autonomous software agents.

From Artificial Intelligence (AI) point of view, bargaining is a rivalry between intelligent agents. Logical reasoning must play an essential role in a bargaining process. A bargaining theory should be able to model both logical reasoning behind bargaining.

This talk gives a brief introduction to a logical theory of bargaining. Instead of abstracting a bargaining problem as a numerical game, we describe bargaining terms and their constraints in logical language. A bargaining problem is then modelled as a vector of sets of ordered bargaining terms in terms of bargainers' preferences. A solution to a bargaining problem is defined as a logically consistent collection of bargaining terms that maximize individual demand and minimize the imbalance of individual satisfaction. Depending on the representation of bargainers' preferences, the characterization of a bargaining solution can be in pure logical axioms or consists of a combination of logical and game-theoretic axioms. The logical theory of bargaining seemingly has offered a new methodology for bargaining analysis therefore could be also applied to the disciplines other than computer science, such as economics, social science and political science.

Partenaires :
Institut de Recherche en Informatique de Toulouse (IRIT)
 
Contact :
Mis à jour le 9 février 2012