Work

An adaptive agent bidding strategy based on stochastic modeling

Year: 1999

Type: conference-paper

Abstract: For a dynamic, evolving multiagent auction, we have developed an adaptive agent bidding strategy (called the p-strategy) based on stochastic modeling.The p-strategy takes into account the dynamics and resulting uncertainties of the auction process using stochastic modeling, and avoids the shortcomings of stochastic modeling by adaptively deciding when to use the model and when not to.Our experiments show that the p-strategy outperforms other candidate bidding strategies in a continuous double auction regardless of the status of the auction and the demography of the agent population.

Source: Adaptive Agents and Multi-Agents Systems

DOI: 10.1145/301136.301181

Authors: Sunju Park, Edmund H. Durfee, William P. Birmingham

Institution: University of Michigan

Language: English

Topic: Auction Theory and Applications

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: bronze

Funders: National Science Foundation, National Aeronautics and Space Administration, Advanced Research Projects Agency

Award: The University of Michigan Digital Libraries Research Proposal