The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Evolutionary Auction Design for Agent-based Marketplaces
|
|
Author(s): Zengchang Qin (University of California, USA)
Copyright: 2008
Pages: 18
Source title:
Agent Systems in Electronic Business
Source Author(s)/Editor(s): Eldon Y. Li (National Chengchi University, Taiwan)and Soe-Tsyr Yuan (National Chengchi University, Taiwan)
DOI: 10.4018/978-1-59904-588-7.ch005
Purchase
|
Abstract
Market mechanism or auction design research is playing an important role in computational economics for resolving multi-agent allocation problems. In this chapter, we review relevant background of trading agents, and market designs by evolutionary computing methods. In particular, a GA can be used to design auction mechanisms in order to automatically generate a desired market mechanism for electronic markets populated with trading agents. In previous research, an auction space model was studied, in which the probability that buyers and sellers are able to quote on a given time step is optimized by a simple GA in order to maximize the market efficiency in terms of Smith’s coefficient of convergence. In this chapter, we also show some new results based on experiments with homogeneous and heterogeneous agents in a more realistic auction space model. This research provides a way of designing efficient auctions by evolutionary computing approaches.
Related Content
|
Emrah Arğın.
© 2022.
16 pages.
|
|
Ebru Gülbuğ Erol, Mustafa Gülsün.
© 2022.
17 pages.
|
|
Yeşim Şener.
© 2022.
18 pages.
|
|
Salim Kurnaz, Deimantė Žilinskienė.
© 2022.
20 pages.
|
|
Dorothea Maria Bowyer, Walid El Hamad, Ciorstan Smark, Greg Evan Jones, Claire Beattie, Ying Deng.
© 2022.
29 pages.
|
|
Savas S. Ates, Vildan Durmaz.
© 2022.
24 pages.
|
|
Nusret Erceylan, Gaye Atilla.
© 2022.
20 pages.
|
|
|