Qualitative and Quantitative Practical Reasoning

Multisensor data fusion in situation assessment processes.- Dependency mining in relational databases.- Syntactic combination of uncertain information: A possibilistic approach.- A coherence-based approach to default reasoning.- A syntactical approach to data fusion.- Some experimental results on learning probabilistic and possibilistic networks with different evaluation measures.- Information fusion in logic: A brief overview.- Focusing vs. belief revision: A fundamental distinction when dealing with generic knowledge.- Background and perspectives of possibilistic graphical models.- Checking several forms of consistency in nonmonotonic knowledge-bases.- The ?-junctions: Combination operators applicable to belief functions.- Just how stupid is postmodernism?.- Integrating preference orderings into argument-based reasoning.- Assumption-based modeling using ABEL.- Propositional quantification for conditional logic.- Fast-division architecture for Dempster-Shafer belief functions.- Graduality by means of analogical reasoning.- Reasoning about unpredicted change and explicit time.- Non-elementary speed-ups in default reasoning.- A compositional reasoning system for executing nonmonotonic theories of reasoning.- Structured belief bases: A practical approach to prioritised base revision.- Entrenchment relations: A uniform approach to nonmonotonicity.- A modal logic for reasoning about knowledge and time on binary subset trees.- How to change factual beliefs using laws and dependence information.- Using default logic for lexical knowledge.- A layered, any time approach to sensor validation.- TreeNets: A framework for anytime evaluation of belief networks.- A logically sound method for uncertain reasoning with quantified conditionals.- Belief functions with nonstandard values.- Error tolerance method in multiple-valued logic.- Representing and reasoning with events from natural language.- Reasoning about security: A logic and a decision method for role-based access

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