Axiomatic characterization of task oriented negotiation

Authors:
Dongmo Zhang
Affiliations:
Intelligent Systems Laboratory, University of Western Sydney, Australia
Venue:
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Year:
2009

Citing 3
Cited 2

Rules of encounter: designing conventions for automated negotiation among computers

Rules of encounter: designing conventions for automated negotiation among computers
Reaching agreements through argumentation: a logical model and implementation

Artificial Intelligence
Extremal behaviour in multiagent contract negotiation

Journal of Artificial Intelligence Research

A logic-based axiomatic model of bargaining

Artificial Intelligence
Efficient issue-grouping approach for multiple interdependent issues negotiation between exaggerator agents

Decision Support Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents an axiomatic analysis of negotiation problems within task-oriented domains (TOD). We start by applying three classical bargaining solutions of Nash, Kalai-Smorodinsky and Egalitarian to the domains of problems with a preprocess of randomization on possible agreements. We find out that these three solutions coincide within any TOD and can be characterized by the same set of axioms, which specify a solution of task oriented negotiation as an outcome of dual-process of maximizing cost reduction and minimizing workload imbalance. This axiomatic characterization is then used to produce an approximate solution to the domain of problems without randomization on possible agreements.