Proceedings of the ISSEK94 Workshop on Mathematical and Statistical Methods in Artificial Intelligence

Front Matter....Pages ii-viii
Fuzzy Specification of Uncertain Knowledge and Vague or Imprecise Information....Pages 1-21
Some Notes on Possibilistic Learning....Pages 23-32
Statistics with Fuzzy Data....Pages 33-49
Operative Controlling Based on Bayesian Networks Using the Kalman Filter Technique....Pages 51-58
Construction, Simulation and Testing of Causal Probabilistic Networks....Pages 59-87
Conditional Events and Probability in the Approach to Artificial Intelligence through Coherence....Pages 89-104
Abduction and Induction Based on Non-Monotonic Reasoning....Pages 105-118
Independence Relationships in Possibility Theory and Their Application to Learning Belief Networks....Pages 119-130
Using Abduction to Learn Horn Theories....Pages 131-146
On Logics of Approximate Reasoning II....Pages 147-155
Based Revision Operations and Schemes: Semantics, Representation, and Complexity....Pages 157-170
On the Notion of Similarity in Case-Based Reasoning....Pages 171-183
Linear Space Induction in First Order Logic with Relieff....Pages 185-198
Induction of Decision Trees Using Relieff....Pages 199-220
Representing Examples by Examples....Pages 221-235
Green Coffee Grading Using Fuzzy Classification....Pages 237-245
Learning from Noisy Medical Data: A Comparative Study Based on a Real Diagnostic Problem....Pages 247-256