scholarly journals A fuzzy-logic based bidding strategy for autonomous agents in continuous double auctions

2003 ◽  
Vol 15 (6) ◽  
pp. 1345-1363 ◽  
Author(s):  
Minghua He ◽  
Ho-fung Leung ◽  
N.R. Jennings
Keyword(s):  
Fuzzy Logic ◽  
Autonomous Agents ◽  
Bidding Strategy ◽  
Double Auctions ◽  
Continuous Double Auctions

Fuzzy logic-based bidding strategies in dynamic double auctions

Kybernetes ◽  
2019 ◽  
Vol 48 (3) ◽  
pp. 612-635
Author(s):  
Baki Unal ◽  
Çagdas Hakan Aladag
Keyword(s):  
Fuzzy Logic ◽  
Bidding Strategy ◽  
Double Auction ◽  
Auction Markets ◽  
Content Type ◽  
Bidding Strategies ◽  
Double Auctions ◽  
Inference Systems ◽  
Zero Intelligence ◽  
Logic Inference

Purpose Double auctions are widely used market mechanisms on the world. Communication technologies such as internet increased importance of this market institution. The purpose of this study is to develop novel bidding strategies for dynamic double auction markets, explain price formation through interactions of buyers and sellers in decentralized fashion and compare macro market outputs of different micro bidding strategies. Design/methodology/approach In this study, two novel bidding strategies based on fuzzy logic are presented. Also, four new bidding strategies based on price targeting are introduced for the aim of comparison. The proposed bidding strategies are based on agent-based computational economics approach. The authors performed multi-agent simulations of double auction market for each suggested bidding strategy. For the aim of comparison, the zero intelligence strategy is also used in the simulation study. Various market outputs are obtained from these simulations. These outputs are market efficiencies, price means, price standard deviations, profits of sellers and buyers, transaction quantities, profit dispersions and Smith’s alpha statistics. All outputs are also compared to each other using t-tests and kernel density plots. Findings The results show that fuzzy logic-based bidding strategies are superior to price targeting strategies and the zero intelligence strategy. The authors also find that only small number of inputs such as the best bid, the best ask, reference price and trader valuations are sufficient to take right action and to attain higher efficiency in a fuzzy logic-based bidding strategy. Originality/value This paper presents novel bidding strategies for dynamic double auction markets. New bidding strategies based on fuzzy logic inference systems are developed, and their superior performances are shown. These strategies can be easily used in market-based control and automated bidding systems.

scholarly journals Use of Markov Chains to Design an Agent Bidding Strategy for Continuous Double Auctions

2004 ◽  
Vol 22 ◽  
pp. 175-214 ◽  
Author(s):  
S. Park ◽  
E. H. Durfee ◽  
W. P. Birmingham
Keyword(s):  
Time Horizon ◽  
Markov Chain Model ◽  
The Other ◽  
Bidding Strategy ◽  
Chain Model ◽  
Double Auctions ◽  
Continuous Double Auctions ◽  
Heuristic Strategies ◽  
Bid Price ◽  
New Strategy

As computational agents are developed for increasingly complicated e-commerce applications, the complexity of the decisions they face demands advances in artificial intelligence techniques. For example, an agent representing a seller in an auction should try to maximize the seller?s profit by reasoning about a variety of possibly uncertain pieces of information, such as the maximum prices various buyers might be willing to pay, the possible prices being offered by competing sellers, the rules by which the auction operates, the dynamic arrival and matching of offers to buy and sell, and so on. A naive application of multiagent reasoning techniques would require the seller?s agent to explicitly model all of the other agents through an extended time horizon, rendering the problem intractable for many realistically-sized problems. We have instead devised a new strategy that an agent can use to determine its bid price based on a more tractable Markov chain model of the auction process. We have experimentally identified the conditions under which our new strategy works well, as well as how well it works in comparison to the optimal performance the agent could have achieved had it known the future. Our results show that our new strategy in general performs well, outperforming other tractable heuristic strategies in a majority of experiments, and is particularly effective in a 'seller?s market', where many buy offers are available.

Automated Fuzzy Bidding Strategy for Continuous Double Auctions Using Trading Agent’s Attitude and Market Competition

2010 ◽  
Vol 2 (4) ◽  
pp. 56-74 ◽  
Author(s):  
Madhu Goyal ◽  
Saroj Kaushik ◽  
Preetinder Kaur
Keyword(s):  
Direct Method ◽  
Market Competition ◽  
Bidding Strategy ◽  
Double Auctions ◽  
Continuous Double Auctions ◽  
Two Factors ◽  
Bidding Agents ◽  
Continuous Double Auction ◽  
Transaction Price ◽  
Bidding Process

This paper designs a novel fuzzy competition and attitude based bidding strategy (FCA-Bid) for continuous double auction in which the best transaction price is calculated on account of the attitude of the agents and the competition for the goods in the market. The estimation of attitude is based on the bidding item’s attribute assessment, which adapts the fuzzy sets technique to handle uncertainty of the bidding process. Additionally, it uses heuristic rules to determine the attitude of bidding agents. The bidding strategy also uses and determines competition in the market (based on the two factors, number of the bidders participating and the total time elapsed for an auction) using Mamdani’s Direct Method. Then the range for the trading price will be determined based on the assessed attitude and the competition in the market using the fuzzy reasoning technique. The final transaction price is calculated after considering the conflicting attitudes of the seller and the bidder toward selecting the transaction price.

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