Comparison of fuzzy implication operators by means of weighting strategy in resolution based automated reasoning
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[1] Ross A. Overbeek,et al. Complexity and related enhancements for automated theorem-proving programs , 1976 .
[2] Larry Wos,et al. Automated reasoning (2nd ed.): introduction and applications , 1992 .
[3] L. J. Kohout,et al. Knowledge Representation in Medicine and Clinical Behavioural Science , 1986 .
[4] Larry Wos,et al. Automated Reasoning: Introduction and Applications , 1984 .
[5] John F. Sowa,et al. Logical foundations of artificial intelligence: Michael R. Genesereth and Nils J. Nilsson, (Morgan Kaufmann, Los Altos, CA, 1987); 406 + xviii pages , 1989 .
[6] William McCune,et al. OTTER 1.0 Users' Guide , 1990 .
[7] Ronald R. Yager,et al. Uncertainty in Knowledge-Based Systems , 1987, Lecture Notes in Computer Science.
[8] Ladislav J. Kohout,et al. The use of fuzzy information retrieval techniques in construction of multi-centre knowledge-based systems , 1986, IPMU.
[9] L. Kohout,et al. Special properties, closures and interiors of crisp and fuzzy relations , 1988 .
[10] Yong-Gi Kim. Use of fuzzy relational information retrieval technique for generating control strategies in resolution-based automated reasoning , 1992 .
[11] Michael R. Genesereth,et al. Logical foundations of artificial intelligence , 1987 .
[12] Yoshiaki Shirai,et al. Artificial Intelligence: Concepts, Techniques, and Applications , 1984 .
[13] Bertram Raphael,et al. The use of theorem-proving techniques in question-answering systems , 1968, ACM National Conference.
[14] L. Kohout,et al. FUZZY POWER SETS AND FUZZY IMPLICATION OPERATORS , 1980 .
[15] Ladislav J. Kohout. A perspective on intelligent systems: a framework for analysis and design , 1990 .