- Title
- A comparison of bidding strategies for online auctions using fuzzy reasoning and negotiation decision functions
- Creator
- Kaur, Preetinder; Goyal, Madhu; Lu, Jie
- Date
- 2017
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/159259
- Identifier
- vital:11953
- Identifier
-
https://doi.org/10.1109/tfuzz.2016.2598297
- Identifier
- ISSN:1063-6706
- Abstract
- Bidders often feel challenged when looking for the best bidding strategies to excel in the competitive environment of multiple and simultaneous online auctions for same or similar items. Bidders face complicated issues for deciding which auction to participate in, whether to bid early or late, and how much to bid. In this paper, we present the design of bidding strategies, which aim to forecast the bid amounts for buyers at a particular moment in time based on their bidding behavior and their valuation of an auctioned item. The agent develops a comprehensive methodology for final price estimation, which designs bidding strategies to address buyers' different bidding behaviors using two approaches: Mamdani method with regression analysis and negotiation decision functions. The experimental results show that the agents who follow fuzzy reasoning with a regression approach outperform other existing agents in most settings in terms of their success rate and expected utility.
- Publisher
- IEEE
- Relation
- IEEE Transactions on Fuzzy Systems Vol. 25, no. 2 (2017), p. 425-438
- Rights
- Copyright © 2016 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.
- Rights
- Open Access
- Rights
- This metadata is freely available under a CCO license
- Subject
- 0102 Applied Mathematics; 0801 Artificial Intelligence and Image Processing; 0906 Electrical and Electronic Engineering; E-commerce; Fuzzy reasoning; Multiple linear regression; Negotiation decision functions (NDFs); Online auctions; Software agents
- Full Text
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