Logic versus Approximation

Nowadays knowledge-based systems research and development essentially employs two paradigms of reasoning. There are on the one hand the logic-based approaches where logic is to be understood in a rather broad sense; usually these approaches are used in symbolic domains where numerical calculations are not the core challenge. On the other hand we find approximation oriented reasoning; methods of these kinds are mainly applied in numerical domains where approximation is part of the scientific methodology itself.

However, from an abstract level all these approaches do focus on similar topics and arise on various levels such as problem modeling, inference and problem solving techniques, algorithms and mathematical methods, mathematical relations between discrete and continuous properties, and are integrated in tools and applications. In accordance with the unifying vision and research interest of Michael M. Richter and in correspondence to his scientific work, this book presents 13 revised full papers advocating the integration of logic-based and approximation-oriented approaches in knowledge processing.

Inhalt

A True Unprovable Formula of Fuzzy Predicate Logic.- The Inherent Indistinguishability in Fuzzy Systems.- On Models for Quantified Boolean Formulas.- Polynomial Algorithms for MPSP Using Parametric Linear Programming.- Discrete and Continuous Methods of Demography.- Computer Science between Symbolic Representation and Open Construction.- Towards a Theory of Information.- Retrieval by Structure from Chemical Data Bases.- Engineers Don't Search.- Randomized Search Heuristics as an Alternative to Exact Optimization.- Approximation of Utility Functions by Learning Similarity Measures.- Knowledge Sharing in Agile Software Teams.- Logic and Approximation in Knowledge Based Systems.