Adaptive agent bidding strategy based on stochastic modeling

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

Research output: Contribution to conferencePaper

36 Citations (Scopus)

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.

Original languageEnglish
Pages147-153
Number of pages7
Publication statusPublished - 1999 Jan 1
EventProceedings of the 1999 3rd International Conference on Autonomous Agents - Seattle, WA, USA
Duration: 1999 May 11999 May 5

Conference

ConferenceProceedings of the 1999 3rd International Conference on Autonomous Agents
CitySeattle, WA, USA
Period99/5/199/5/5

    Fingerprint

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

Park, S., Durfee, E. H., & Birmingham, W. P. (1999). Adaptive agent bidding strategy based on stochastic modeling. 147-153. Paper presented at Proceedings of the 1999 3rd International Conference on Autonomous Agents, Seattle, WA, USA, .