Foundations of Reasoning under Uncertainty

ISBN-13: 9783642262357 / Angielski / Miękka / 2012 / 265 str.

Bernadette Bouchon-Meunier;Luis Magdalena;Manuel Ojeda-Aciego

Opis

Uncertainty exists almost everywhere, except in the most idealized situations; it is not only an inevitable and ubiquitous phenomenon, but also a fundamental sci- ti?c principle. Furthermore, uncertainty is an attribute of information and, usually, decision-relevant information is uncertain and/or imprecise, therefore the abilities to handle uncertain information and to reason from incomplete knowledge are c- cial features of intelligent behaviour in complex and dynamic environments. By carefully exploiting our tolerance for imprecision and approximation we can often achieve tractability, robustness, and better descriptions of reality than traditional - ductive methods would allow us to obtain. In conclusion, as we move further into the ageofmachineintelligence, theproblemofreasoningunderuncertainty, in other words, drawing conclusions from partial knowledge, has become a major research theme. Not surprisingly, the rigoroustreatment of uncertaintyrequiressophisticated - chinery, and the present volume is conceived as a contribution to a better und- standing of the foundations of information processing and decision-making in an environment of uncertainty, imprecision and partiality of truth. This volume draws on papers presented at the 2008 Conference on Information Processing and Management of Uncertainty (IPMU), held in Malaga, Spain, or- nized by the University of Mal aga. The conference brought together some of the world's leading experts in the study of uncertainty.

Spis treści

Linear Fuzzy Regression Using Trapezoidal Fuzzy Intervals.- Fundamentals for Design and Construction of a Fuzzy Random Forest.- Mining Exception Rules.- Degrees of Truth, Ill-Known Sets and Contradiction.- Algorithms for Trapezoidal Approximations of Fuzzy Numbers Preserving the Expected Interval.- Possibilistic Similarity Measures.- Efficient Thresholded Tabulation for Fuzzy Query Answering.- Linguistic Summaries of Time Series: On Some Additional Data Independent Quality Criteria.- Preference Modelling Using the Level-Dependent Choquet Integral with Respect to ?ukasiewicz Filters.- Majority Rules Generated by Mixture Operators.- Belief Function Correction Mechanisms.- A Comparison of Conditional Coherence Concepts for Finite Spaces.- On Evidential Markov Chains.

Blurb

This volume draws on papers presented at the 2008 Conference on Information Processing and Management of Uncertainty (IPMU), held in Málaga, Spain, organized by the University of Málaga. The conference brought together some of the world’s leading experts in the study of uncertainty.

Since its first edition, held in 1986, the focus of IPMU conferences has been on the development of foundations and technology needed for the construction of intelligent systems. Over the years, IPMU has grown steadily in visibility and importance, and has evolved into a leading conference in its field, embracing a wide variety of methodologies for dealing with uncertainty and imprecision, and this explains the unusually wide variety of concepts, methods and techniques which are discussed in the book. The growth in importance of IPMU reflects the fact that as we move further into the age of machine intelligence and mechanized decisionmaking, the issue of how to deal with uncertain information becomes an issue of paramount concern.