Paper Info
Title
Optimization of multiple related negotiation through multi-negotiation network
Abstract
In this paper, a Multi-Negotiation Network (MNN) and a Multi-Negotiation Influence Diagram (MNID) are proposed to optimally handle Multiple Related Negotiations (MRN) in a multi-agent system. Most popular, state-of-the-art approaches perform MRN sequentially. However, a sequential procedure may not optimally execute MRN in terms of maximizing the global outcome, and may even lead to unnecessary losses in some situations. The motivation of this research is to use a MNN to handle MRN concurrently so as to maximize the expected utility of MRN. Firstly, both the joint success rate and the joint utility by considering all related negotiations are dynamically calculated based on a MNN. Secondly, by employing a MNID, an agent's possible decision on each related negotiation is reflected by the value of expected utility. Lastly, through comparing expected utilities between all possible policies to conduct MRN, an optimal policy is generated to optimize the global outcome ofMRN. The experimental results indicate that the proposed approach can improve the global outcome of MRN in a successful end scenario, and avoid unnecessary losses in an unsuccessful end scenario.
Year
Venue
Keywords
2010
KSEM
global outcome ofmrn,mrn sequentially,unnecessary loss,multiple related negotiation,multi-negotiation network,related negotiation,mrn concurrently,joint utility,multi-negotiation influence diagram,global outcome,expected utility,multi agent system,influence diagram
Field
DocType
Volume
Mathematical optimization,Expected utility hypothesis,Computer science,Real-time computing,Influence diagram,Artificial intelligence,Machine learning,Negotiation
Conference
6291.0
ISSN
ISBN
Citations 
0302-9743
3-642-15279-1
1
PageRank 
References 
Authors
0.34
10
4
Name
Order
Citations
PageRank
Fenghui Ren115320.05
Minjie Zhang225530.01
Chunyan Miao32307195.72
Zhiqi Shen4114882.57