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Knowledge and Information Systems

, Volume 3, Issue 2, pp 225–251 | Cite as

ActiveCBR: An Agent System That Integrates Case-Based Reasoning and Active Databases

  • Sheng Li
  • Qiang Yang
Regular Paper

Abstract.

Case-based reasoning (CBR) is an artificial intelligence (AI) technique for problem solving that uses previous similar examples to solve a current problem. Despite its success, most current CBR systems are passive: they require human users to activate them manually and to provide information about the incoming problem explicitly. In this paper, we present an integrated agent system that integrates CBR systems with an active database system. Active databases, with the support of active rules, can perform event detection, condition monitoring, and event handling (action execution) in an automatic manner. The integrated ActiveCBR system consists of two layers. In the lower layer, the active database is rule-driven; in the higher layer, the result of action execution of active rules is transformed into feature–value pairs required by the CBR subsystem. The layered architecture separates CBR from sophisticated rule-based reasoning, and improves the traditional passive CBR system with the active property. The system has both real-time response and is highly exible in knowledge management as well as autonomously in response to events that a passive CBR system cannot handle. We demonstrate the system efficiency and effectiveness through empirical tests.

Keywords: Active databases; Agent system; Case-based reasoning 

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Copyright information

© Springer-Verlag London Limited 2001

Authors and Affiliations

  • Sheng Li
    • 1
  • Qiang Yang
    • 1
  1. 1.School of Computing Science, Simon Fraser University, Burnaby, BC, CanadaCA

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