A philosophical basis for knowledge acquisition
Knowledge Acquisition
Incremental acquisition of search knowledge
International Journal of Human-Computer Studies
Uncovering the Conceptual Models in Ripple Down Rules
ICCS '97 Proceedings of the Fifth International Conference on Conceptual Structures: Fulfilling Peirce's Dream
Discovery of Class Relations in Exception Structured Knowledge Bases
ICCS '00 Proceedings of the Linguistic on Conceptual Structures: Logical Linguistic, and Computational Issues
Combining knowledge acquisition and machine learning to control dynamic systems
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Incremental knowledge acquisition using generalised RDR for soccer simulation
PKAW'10 Proceedings of the 11th international conference on Knowledge management and acquisition for smart systems and services
Simulated assessment of ripple round rules
PKAW'10 Proceedings of the 11th international conference on Knowledge management and acquisition for smart systems and services
User behavior analysis of the open-ended document classification system
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
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Ripple-Down Rules (RDR) has the goal of simple, incremental development of a knowledge-based system (KBS) while the KBS is already in use, so that over time an expert can evolve a sophisticated KBS as a minor extension of their normal duties. RDR has had considerable success in developing classification KBS. It has been extended to configuration, heuristic search and other tasks. This paper proposes a generalisation of RDR that may enable experts to evolve KBS for a range of tasks.