Efficient statistical methods for evaluating trading agent performance

Eric Sodomka, John Collins, Maria L Gini

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Scopus citations

Abstract

Market simulations, like their real-world counterparts, are typically domains of high complexity, high variability, and incomplete information. The performance of autonomous agents in these markets depends both upon the strategies of their opponents and on various market conditions, such as supply and demand. Because the space for possible strategies and market conditions is very large, empirical analysis in these domains becomes exceedingly difficult. Researchers who wish to evaluate their agents must run many test games across multiple opponent sets and market conditions to verify that agent performance has actually improved. Our approach is to improve the statistical power of market simulation experiments by controlling their complexity, thereby creating an environment more conducive to structured agent testing and analysis. We develop a tool that controls variability across games in one such market environment, the Trading Agent Competition for Supply Chain Management (TAC SCM), and demonstrate how it provides an efficient, systematic method for TAC SCM researchers to analyze agent performance.

Original languageEnglish (US)
Title of host publicationAAAI-07/IAAI-07 Proceedings
Subtitle of host publication22nd AAAI Conference on Artificial Intelligence and the 19th Innovative Applications of Artificial Intelligence Conference
Pages770-775
Number of pages6
Volume1
StatePublished - Nov 28 2007
EventAAAI-07/IAAI-07 Proceedings: 22nd AAAI Conference on Artificial Intelligence and the 19th Innovative Applications of Artificial Intelligence Conference - Vancouver, BC, Canada
Duration: Jul 22 2007Jul 26 2007

Other

OtherAAAI-07/IAAI-07 Proceedings: 22nd AAAI Conference on Artificial Intelligence and the 19th Innovative Applications of Artificial Intelligence Conference
CountryCanada
CityVancouver, BC
Period7/22/077/26/07

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