Learning Business Strategies for Competitive Electronic Marketplaces

Author

Praça, Isabel ; Viamonte, Maria João ; Ramos, Carlos ; Vale, Zita

Author_Institution

Knowledge Eng. & Decision Support Res. Group, Inst. of Eng. of Porto, Porto

Volume

2

fYear

2007

fDate

21-23 May 2007

Firstpage

611

Lastpage

616

Abstract

This paper presents a Multi-Agent Market simulator designed for developing new agent market strategies based on a complete understanding of buyer and seller behaviors, preference models and pricing algorithms, considering user risk preferences and game theory for scenario analysis. This tool studies negotiations based on different market mechanisms and, time and behavior dependent strategies. The results of the negotiations between agents are analyzed by data mining algorithms in order to extract rules that give agents feedback to improve their strategies. The system also includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions, and capable of considering other agent reactions.

Keywords

data mining; electronic commerce; game theory; multi-agent systems; pricing; agent market strategies; business strategies; competitive electronic marketplaces; data mining algorithms; game theory; multiagent market simulator; pricing algorithms; Algorithm design and analysis; Analytical models; Consumer electronics; Data analysis; Data mining; Electricity supply industry; Feedback; Game theory; Knowledge engineering; Risk analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Advanced Information Networking and Applications Workshops, 2007, AINAW '07. 21st International Conference on

Conference_Location

Niagara Falls, Ont.

Print_ISBN

978-0-7695-2847-2

Type

conf

DOI

10.1109/AINAW.2007.219

Filename

4224171