Abstract
Almost all existing methodologies and automated tools for knowledge acquisition are somehow based on classical mathematical logic or its various classical conservative extensions. This paper proposes a new approach to knowledge acquisition problem: automated knowledge acquisition by relevant reasoning based on strong relevant logic. The paper points out why any of the classical mathematical logic, its various classical conservative extensions, and traditional relevant logics is not a suitable logical basis for knowledge acquisition, shows that strong relevant logic is a more hopeful candidate for the purpose, and establishes a conceptional foundation for automated knowledge acquisition by relevant reasoning based on strong relevant logic.
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Cheng, J. (2003). Automated Knowledge Acquisition by Relevant Reasoning Based on Strong Relevant Logic. In: Palade, V., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2003. Lecture Notes in Computer Science(), vol 2773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45224-9_13
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DOI: https://doi.org/10.1007/978-3-540-45224-9_13
Publisher Name: Springer, Berlin, Heidelberg
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