Decision aggregation in an agent-based financial investment planning system

Zhang, Zili 2006, Decision aggregation in an agent-based financial investment planning system, Lecture notes in computer science, vol. 3885, pp. 179-190.

Attached Files
Name Description MIMEType Size Downloads

Title Decision aggregation in an agent-based financial investment planning system
Author(s) Zhang, Zili
Journal name Lecture notes in computer science
Volume number 3885
Start page 179
End page 190
Publisher Springer-Verlag
Place of publication Heidelberg, Germany
Publication date 2006
ISSN 0302-9743
1611-3349
Keyword(s) multi-agent systems
intelligent agents
financial investment planning
decision aggregation
ordered weighted averaging operator
Summary Agent technology provides a new way to model many complex problems like financial investment planning. With this observation in mind, a financial investment planning system was developed from agent perspectives with 12 different agents integrated. Some of the agents have similar problem solving and decision making capabilities. The results from these agents require to be combined. Ordered Weighted Averaging (OWA) operator was chosen to aggregate different results. Details on how OWA was applied as well as appropriate evaluation are presented.
Language eng
Field of Research 080105 Expert Systems
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2006, Springer-Verlag
Persistent URL http://hdl.handle.net/10536/DRO/DU:30003576

Document type: Journal Article
Collection: School of Engineering and Information Technology
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Access Statistics: 345 Abstract Views, 0 File Downloads  -  Detailed Statistics
Created: Mon, 07 Jul 2008, 08:57:05 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.