Advances in Intelligent Computing - IPMU '94

This book presents a topical selection of full refereed research papers presented during the 5th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU '94, held in Paris, France in July 1994. The topical focus is on the role of uncertainty in the contruction of intelligent computing systems and it is shown how the concepts of AI, neural networks, and fuzzy logic can be utilized for that purpose.
In total, there are presented 63 thoroughly revised papers organized in sections on fundamental issues; theory of evidence; networks, probabilistic, statistical, and informational methods; possibility theory, logics, chaos, reusability, and applications.

Philosophical foundations for causal networks.- Non standard probabilistic and non probabilistic representations of uncertainty.- Argumentation systems and evidence theory.- Algebraic structures related to Dempster-Shafer theory.- Extension of lower probabilities and coherence of belief measures.- A note on multi-objective information measures.- Decision making using belief functions evaluation of information.- Hybrid propagation in junction trees.- Heuristic algorithms for the triangulation of graphs.- Computing marginals from the marginal representation in Markov trees.- Representation of Bayesian networks as relational databases.- Decision influence diagrams with fuzzy utilities.- Causal Networks and their toolkit in KSE.- Approximations of causal networks by polytrees: an empirical study.- Evidence propagation on influence diagrams and value of evidence.- Some varieties of qualitative probability.- The qualitative verification of quantitative uncertainty.- Uncertainty management using probability intervals.- Probabilistic consistency of conditional probability bounds.- Testing the convenience of a variate for stratification in estimating the Gini-Simpson diversity.- Fuzzy probabilities and their applications to statistical inference.- A bayesian functional approach to fuzzy system representation.- Information matrices associated to (h, ?)-divergence measures: Applications to testing hypotheses.- Informational energy test for equality of variances.- Compositive information measure of a fuzzy set.- Informational time.- Updating, transition constraints and possibilistic Markov chains.- Possibilistic logic as interpretability logic.- A numerical framework for possibilistic abduction.- Possibility theory and independence.- Handling hard rules and default rules in possibilistic logic.- A general possibilistic framework for reliability theory.- Possibilistic semantic nets.- An essay on name and extension of rule-given properties.- On non-alethic logic.- Marginal problem in different calculi of AI.- Implication connectives for logics with right weakening.- Stochastic logic.- An approach to handle partially sound rules of inference.- Using classical theorem-proving techniques for approximate reasoning: Revised report.- Translation-based deduction methods for modal logics.- A system of knowledge representation based on formulae of predicate calculus whose variables are annotated by expressions of a “fuzzy” Terminological Logic.- Using preference based heuristics to control abductive reasoning.- Efficient interpretation of prepositional multiple-valued logic programs.- Many-valued epistemic states. An application to a reflective architecture: Milord-II.- Acoustical chaotic fractal images for medical imaging.- Chaos causes perspective reversals for ambiguious patterns.- Implications of a continuous approach to chaotic modeling.- “Homeostasic” control of imbalanced strangeattractors with or without asking to a change in chaotic dynamics.- A feature based reuse library.- Managing uncertainty in an object recovery process.- Juggling in free fall: Uncertainty management aspects of domain analysis methods.- Hybrid fuzzy metrics for software reusability.- A program transformation system for software reuse.- Abstract visualization of software.- Retrieval of images using Pixel based object models.- Object recognition based on pattern features.- Key-picture selection for the analysis of visual speech with fuzzy methods.- Effective scheduling of tasks under weak temporal interval constraints.- Introducing contextual information in multisensor tracking algorithms.- FAM on grain scheduling control of highly nonlinear and disturbed processes.- How to choose according to partial evaluations?.- The role of measurement uncertainty in numeric law induction.