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A variety of formalisms have been developed to address suchaspects of handling imperfect knowledge as uncertainty,vagueness, imprecision, incompleteness, and partialinconsistency. Some of the most familiar approaches in thisresearch field are nonmonotonic logics, modal logics,probability theory (Bayesian and non-Bayesian), belieffunction theory, and fuzzy sets and possibility theory.ESPRIT Basic Research Action 3085, entitled DefeasibleReasoning and Uncertainty Management Systems (DRUMS), aimsto contribute to the elucidation of similarities anddifferences between these formalisms. It consists of 11active European research groups. The European Conference onSymbolic and Quantitative Approaches to Uncertainty (ESQAU)provides a forum for these groups to meet and discuss theirscientific results.This volume contains 42 contributions accepted for the ESQAUmeeting held in October 1991 in Marseille, together with 12articles presenting the activities of the DRUMS groups andtwo invited presentations.
Inhaltsverzeichnis
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 expert system shell.- Induction of uncertain rules and the sociopathicity property in Dempster-Shafer theory.- Hierarchical default logic.- A logic of imprecise monadic predicates and its relation to the S5-modal fuzzy logic.- Every complex system can be determined by a causal probabilistic network without cycles and every such network determines a Markov field.- Probabilistic default reasoning involving continuous variables.- Revision in propositional calculus.- A constraint-based approach to uncertain and imprecise reasoning. Application to expert systems.- Random closed sets: A unified approach to the representation of imprecision and uncertainty.- Knowledge extraction in trivalued propositional logic.- Using maximum entropy to identify unsafe assumptions in probabilistic expert systems.- On truth and utility.- On commitment and cumulativity in default logics.- A tableau-based characterisation for default logic.- Restraining the proliferation of worlds in probabilistic logic entailments.- Managing uncertainty in environmental analysis: An application to measurement data interpretation.- Handling uncertainty in knowledge-based computer vision.- Probabilistic reasoning with facts and rules in deductive databases.- An entity-relationship approach to the modelling of vagueness in databases.- A preferential model semantics for default logic.- Elementary hyperentailment.
Über den Autor / die Autorin
Prof. Dr. Rudolf Kruse ist Leiter des Lehrstuhls für Neuro-Fuzzy-Systeme an der Universität Magdeburg.
