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Diagnostic problem solving using first principles and heuristics

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Abstract

This paper proposes an approach to diagnostic reasoning with the following distinct features: 1 A diagnostic system is formulated in FOL with equality, particularly in the form of program clauses; 2 The abnormality of system components is determined in terms of either experiential knowledge of domain experts or behavioral description of components; 3 Heuristics is fully used not only to assist in judging the abnormality of system components, but also to guide the diagnosis; 4 A unique diagnosis will be computed for a given observation, provided that certain essential I-O information is supplemented when demanded.

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Authors and Affiliations

  1. Department of Computer Science, Chongqing University, 630044, Chongqing

    Shen Yidong & Rong Mei

  2. Department of Computer Science, Shanghai University of Science and Technology, 201800, Shanghai

    Tong Fu

Authors
  1. Shen Yidong
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  2. Rong Mei
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  3. Tong Fu
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Additional information

This research is supported by the National Natural Science Foundation of China.

Shen Yidong, Ph.D., is a Professor of Computer Science at Chongqing University, China. His present research interests include artificial intelligence, deductive/object-oriented/heterogeneous databases, logic programming and parallel processing.

Rong Mei is a Doctor of Computer Science at Chongqing University, China. Her present research interests include artificial intelligence, qualitative reasoning, deductive databases.

Tong Fu is a Professor of Computer Science at Shanghai University of Science and Technology. His present research interests include artificial intelligence, engineering deductive databases, CIMS and distributed systems.

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Shen, Y., Rong, M. & Tong, F. Diagnostic problem solving using first principles and heuristics. J. of Comput. Sci. & Technol. 11, 372–384 (1996). https://doi.org/10.1007/BF02948481

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  • DOI: https://doi.org/10.1007/BF02948481

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