IPMU '92 - advanced methods in artificial intelligence : 4th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, Palma de Mallorca, Spain, July 6 10, 1992 : proceedings

The papers in this volume are extended versions of presentations at the fourth International Conference on Information Processing and Management of Uncertainty in Knowledge-based Systems (IPMU), held in Palma de Mallorca, July 6-10, 1992. The conference focused on issues related to the acquisition,...

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Yhteisötekijä: International conference on information processing and management of uncertainty in knowledge-based systems :Majorque, Espagne
Muut tekijät: Bouchon-Meunier, Bernadette, 1948- (Päätoimittaja), Valverde, Llorenç (Päätoimittaja), Yager, Ronald R., 1941- (Päätoimittaja)
Aineistotyyppi: Livre numérique
Kieli:Anglais
Julkaistu: Berlin [etc.] : Springer [20..].
Cham : Springer Nature
Sarja:Lecture notes in computer science 682
Aiheet:
Linkit:Accès sur la plateforme de l'éditeur
Accès sur la plateforme Istex
Accès Université d'Orléans
Accès INSA CVL
Huomautus: Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• IPMU '92, advanced methods in artificial intelligence, 4th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, Palma de Mallorca, Spain, July 6-10, 1992, proceedings, B. Bouchon-Meunier, L. Valverde, R.R. Yager, eds, Berlin, Springer, 1993, 1 vol. (IX-367 p.), Lecture notes in computer science, 3-540-56735-6
• IPMU'92 - Advanced Methods in Artificial Intelligence, Texte imprimé, 9783662192146
Sisällysluettelo:
  • 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.