Mutli-agent negotiation of fair contracts

Kallel, Omar; Jaâfar, Inès Ben; Dupont, Lionel; Ghédira, Khaled

doi:10.1109/iccie.2010.5668295

Cited by 1 publication

(3 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…-Normal: the negotiator agent has to evolve normally; when an offer is received, the counter-offer is made using the following concession function [7]:…”

Section: Fuzzy Guidance Strategies For Fair Multi-agent Negotiation Omentioning

confidence: 99%

“…In order to evaluate the fairness of both models, we introduce the following criteria [7]: success of the negotiation, the fairness average criterion and the worst unfair criterion.…”

Section: R6: If Progress Is Advanced and Rate Is (Acceptable And Not(mentioning

confidence: 99%

“…The most convenient value is 0.2. -More concessions: the negotiator agent has to make more concessions by doing a double concession(7).…”

mentioning

confidence: 99%

See 2 more Smart Citations

Fuzzy guidance strategies for fair multi-agent negotiation of wholesale price contracts

Kallel

Jaâfar

Dupont

et al. 2011

2011 IEEE International Conference on Industrial Engineering and Engineering Management

View full text Add to dashboard Cite

In this paper, we investigate the negotiation aspect of wholesale price contracts in a supply chain with a retailer buying from several subcontractors. The objective is to help actors in an asymmetric informational context to reach agreements and establish fair contracts. Thus, we present two multi-agent models with the same architecture; a retailer agent negotiating with several subcontractor agents and a fair agent trying to provide some fairness guidance in the negotiation. In the first model (AGS), the fair agent intervenes when an agent makes a relatively low or high offer; he asks this agent to behave differently. In the second model (DGS), the fair agent intervenes when a significant difference appears between the margin rates of the negotiators; he directs them by giving the new rate to apply in the next step. Experiments show more fair results with DGS than AGS.

show abstract

“…-Normal: the negotiator agent has to evolve normally; when an offer is received, the counter-offer is made using the following concession function [7]:…”

Section: Fuzzy Guidance Strategies For Fair Multi-agent Negotiation Omentioning

confidence: 99%

“…In order to evaluate the fairness of both models, we introduce the following criteria [7]: success of the negotiation, the fairness average criterion and the worst unfair criterion.…”

Section: R6: If Progress Is Advanced and Rate Is (Acceptable And Not(mentioning

confidence: 99%