Dynamic Regime Identification and Prediction Based on Observed Behavior in Electronic Marketplaces

Research output: Chapter/Conference proceedingConference proceedingAcademicpeer-review

1 Citation (Scopus)


We present a method for an autonomous agent to identify dominant market conditions, such as oversupply or scarcity. The characteristics of economic regimes are learned from historic data and used, together with real-time observable information, to identify the current market regime and to forecast market changes. The approach is validated with data from the Trading Agent Competition for Supply Chain Management.
Original languageUndefined/Unknown
Title of host publicationAAAI05
Place of PublicationPittsburgh
Number of pages2
Publication statusPublished - 2005
Externally publishedYes

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