Symbolic and Quantitative Approaches to Uncertainty

Abduction in labelled deductive systems a conceptual abstract.- Nonmonotonic inference, expectations, and neural networks.- Imprecise quantifiers and conditional probabilities.- Default logics.- Propagation of uncertainty in dependence graphs.- Efficient algorithms for belief functions based on the relationship between belief and probability.- A brief overview of possibilistic logic.- A modal analysis of possibility theory.- An extended logic language for representing belief.- Graded default logics.- Linguistically expressed uncertainty: Its elicitation and use in modular expert systems.- Reasoning with mass distributions and the context model.- Advance prototyping.- The transferable belief model.- Learning with CASTLE.- A New approach to inference under uncertainty for knowledge based systems.- Learning of uncertain classification rules in medical diagnosis.- Assertional default theories.- The reliability of reasoning with unreliable rules and propositions.- Uncertainty in the valuation of risky assets.- Assessment of qualitative judgements for conditional events in expert systems.- Automated reasoning about an uncertain domain.- Using defeasible logic for a window on a probabilistic database: Some preliminary notes.- From data analysis to uncertainty knowledge analysis.- Difference fuzzy relation equations: Studies in dynamical systems.- Towards a logic for a fuzzy logic controller.- Handling active databases with partial inconsistencies.- An extension of the possibility theory in view of the formalization of approximate reasoning.- Probabilistic regions of persistence.- Formalizing pertinence links in inheritance reasoning: Preliminary report.- A hybrid approach for modeling uncertainty in terminological logics.- Fuzzy control research at Siemens Corporate R&D.- Handling partially ordered defaults in TMS.- Computing extensions of default theories.- An evidential reasoning approach to the classification of satellite images.- PRESS-A probabilistic reasoning

Prof. Dr. Rudolf Kruse ist Leiter des Lehrstuhls für Neuro-Fuzzy-Systeme an der Universität Magdeburg.