Developing a real-time inference approach for rule-based reasoning systems

Authors:
Ying Qiao;Chang Leng;Hongan Wang;Jian Liu
Affiliations:
Beijing Key Lab of Human-computer Interaction, Institute of Software, Beijing, China;Beijing Key Lab of Human-computer Interaction, Institute of Software, Beijing, China;Beijing Key Lab of Human-computer Interaction, Institute of Software, Beijing, China;Shanxi Electric Power Research Institute YouYi East Rd. Xi'an Shan Xi, China
Venue:
Proceedings of the 2013 Research in Adaptive and Convergent Systems
Year:
2013

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Abstract

Rule-based reasoning systems play importance roles for many real-time intelligent systems that need to take time-critical actions in response to the continuously arriving events. In this paper, we propose a novel inference approach, called RTINF to make the reasoning system meet its hard deadlines. A series of simulation studies are conducted to evaluate the performance of RTINF.