IPMU'92 - Advanced Methods in Artificial Intelligence

Possibilistic abduction.- Management of preferences in assumption-based reasoning.- Default exclusion in a KL-ONE-like terminological component.- Unifying various approaches to default logic.- Using maximum entropy in a defeasible logic with probabilistic semantics.- Legality in inheritance networks.- A note on information systems associated to termal algebras.- A backward chaining resolution process involving non-monotonic operators.- On fuzzy conditionals generalising the material conditional.- Integrating resolution—like procedures with Lukasiewicz implication.- The development of a “Logic of Argumentation”.- From “and” to “or”.- Representing spatial and temporal uncertainty.- An analysis of the temporal relations of intervals in relativistic space-time.- Accumulation and inference over finite-generated algebras for mapping approximations.- Similarity measures for case-based reasoning systems.- Statistical methods in learning.- Learning from erroneous examples using fuzzy logic and “textbook” knowledge.- Incremental learning of roughly represented concepts.- Self-organizing qualitative multimodel control.- MoHA, an hybrid learning model.- A new perspective in the inductive acquisition of knowledge from examples.- Knowledge representation through object in the development of expert system chemical synthesis and reaction.- Hierarchical representation of fuzzy if-then rules.- Approximate reasoning in expert systems: Inference and combination tools.- Modes of interval-based plausible reasoning viewed via the checklist paradigm.- Rule-based systems with unreliable conditions.- Fuzzy semantics in expert process control.- Qualitative operators and process engineer semantics of uncertainty.- Facing uncertainty in the management of large irrigation systems: Qualitative approach.- Semantic ambiguity in expert systems: The case of deterministic systems.- A deduction rule for the approximated knowledge of a mapping.- On knowledge base redundancy under uncertain reasoning.- A fuzzy logic approach for sensor validation in real time expert systems.- Application of Neuro-Fuzzy Networks to the identification and control of nonlinear dynamical systems.- Comparison between artificial neural networks and classical statistical methods in pattern recognition.- Learning methods for odor recognition modeling.