Monitoring key company events through deliberative learning

Recent scandals concerning the discovery of fraud committed by a few high profile companies has reinforced a need for innovative approaches to detecting fraudulent company behavior. Fraud detection experts agree that many of the critical clues to fraud, such as frequent management and auditor changes, can be found in qualitative sources such as news articles, press releases, and footnotes accompanying nancial statements. This paper presents a simulated multi-agent system that learns how to collect valuable events from textual sources with pinpoint precision, utilizing the best content providers for each event type while minimizing the overall cost.