ActiveCBR: An Agent System That Integrates Case-Based Reasoning and Active Databases |
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Authors: | Sheng Li Qiang Yang |
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Affiliation: | (1) School of Computing Science, Simon Fraser University, Burnaby, BC, Canada, CA |
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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.
Received 21 April 2000 / Revised 12 June 2000 / Accepted in revised form 14 July 2000 |
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Keywords: | : Active databases Agent system Case-based reasoning |
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