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Nonmonotonic Model Inference-A Formalization of Student Modeling

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Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence. Intelligent Tutoring Systems. Pages 467-475.

Abstract

A student model description language and its synthesis method are presented. The language called SMDL is based on a logic programming language taking 4 truth values such as true, false , unknown and fail. A modeling method called HSMIS is a new nonmonotonic model inference system and has the following major characteristics: ( 1) Model inference of logic program taking 4 truth values, (2)Treatment of nonmonotonicity of both student 's belief and inference process itself. HSMIS incorporates de Kleer's ATMS as a vehicle for formulating the nonmonotonicity. Both SMDL interpreter and HSMIS have been implemented in Common ESP(Extended Self-contained Prolog) and incorporated into a framework for ITS, called FITS.

Mitsuru Ikeda, Yasuyuki Kono, and Riichiro Mizoguchi. 1993. Nonmonotonic Model Inference-A Formalization of Student Modeling. In Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence, IJCAI-93. IJCAI, 467–475. https://ijcai.org/proceedings/1993/66
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