Efficient approximate reasoning with positive and negative information

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3214, Issue , 2004, Pages 779-785

  Cornells, Chris ^a   De Cock, Martine ^a   Kerre, Etienne ^a  

^a GHENT UNIVERSITY   (Belgium)

Author keywords

Approximate reasoning; Inclusion measures; Positive and negative information; Possibility theory

Indexed keywords

APPROXIMATION THEORY; COMPUTATIONAL COMPLEXITY; KNOWLEDGE BASED SYSTEMS;

ALGORITHM COMPLEXITY; APPROXIMATE REASONING; INCLUSION MEASURE; NEGATIVE INFORMATION; POSSIBILITY THEORY; QUANTITATIVE MODELING; REASONING BY ANALOGIES; REASONING METHODS;

FUZZY INFERENCE;

EID: 34247403600     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: None     Document Type: Article

References (4)

1. Bouchon-Meunier B., Dubois, D., Godo, L., Prade, H.: Fuzzy Sets and Possibility Theory in Approximate and Plausible Reasoning. In: Fuzzy sets in approximate reasoning and information systems, Kluwer Academic Publishers (1999) 15-190
2. Cornelis, C.: Two-sidedness in the Representation and Processing of Imprecise Information (in Dutch), Ph. D. thesis, Ghent University
3. Cornelis, C., Kerre, E.E.: Inclusion-Based Approximate Reasoning. In: Lecture Notes in Computer Science 2074 (2001) 221-230
4. Dubois, D., Prade, H., Ughetto, L.: A New Perspective on Reasoning with Fuzzy Rules. In: International Journal of Intelligent Systems 18(5) (2003) 541-563