This volume contains articles accepted for presentation during The Intelligent Information Systems Symposium I1S'2000 which was held in Bystra, Poland, on June 12-16, 2000. This is ninth, in the order, symposium organized by the Institute of Computer Science of Polish Academy of Sciences and devoted to new trends in (broadly understood) Artificial Intelligence. The idea of organizing such meetings dates back to 1992. Our main in tention guided the first, rather small-audience, workshop in the series was to resume the results gained in Polish scientific centers as well as contrast them with the research performed by Polish scientists working at the uni versities in Europe and USA. This idea proved to be attractive enough that we decided to continue such meetings. As the years went by, the workshops has transformed into regular symposia devoted to such fields like Machine Learning, Knowledge Discovery, Natural Language Processing, Knowledge Based Systems and Reasoning, and Soft Computing (Le. Fuzzy and Rough Sets, Bayesian Networks, Neural Networks and Evolutionary Algorithms). At present, about 50 papers prepared by researches from Poland and other countries are usually presented. Besides, for several years now, the symposia are accompanied by a number of tutorials, given by the outstanding scientists in their domain. Up to this year the proceedings were published as our local publication and they were distributed among the scientific libraries. We feel however, that the subject matter as well as the quality of papers is sufficient to present the proceedings to a broader scientific audience.

Klappentext

The book contains a selection of papers presented at the International Symposium IIS'2000 held in Bystra, Poland devoted to broadly understood artificial intelligence. The selected papers report on progress in theory, and applications of Machine Learning, Knowledge Discovery, Natural Language Processing, Knowledge Based Systems and Reasoning, and Soft Computing (i.e. Fuzzy and Rough Sets, Bayesian Networks, Neural Networks, and Evolutionary Algorithms). Applications range from medical diagnosis, processing of financial information, decision making to diagnosis and control of complex technical systems. Practical issues were investigated from various theoretical points of view like automated and semi-automated learning procedures or agent technology. Interesting practical solutions were proposed and challenging new research issues were suggested.

Inhalt
Rule and Decision Tree Acquisition.- Optimization and Interpretation of Rule-based Classifiers.- Comparative Analysis of Selected Association Rules Types.- Data Mining Experiments with the Melanoma Data Set.- Description of the Machine Operation in Varying Conditions with the Use of Dynamic Scene Idea.- Application of Decision Trees to Wavelet-based Classification of Musical Instrument Sounds.- Rough Sets.- Mining for Action-Rules in Large Decision Tables Classifying Customers.- Generation of Exhaustive Rule Sets Using a Reduct Generating Algorithm.- Optimal Decision Making with Data-Acquired Decision Tables.- Unsupervised Learning.- Applying Data Mining Methods for Cellular Radio Network Planning.- SBL-PM: A Simple Algorithm for Selection of Reference Instances for Similarity Based Methods.- Geometrical Approach to a Coherent Set of Operational Definitions.- Generating Optimal Repertoire of Antibody Strings in an Artificial Immune System.- Logical and Methodological Foundations of AI.- Modeling Agent Organizations.- Expressiveness of $-Calculus: What Matters?.- Distributed Artificial Intelligence: A Case Study of Implementations of a Parallel Algorithm Computing All Homomorphisms of Finite Automata.- Methodology of Diagnostic Knowledge Acquisition from Databases of Examples.- Verification of Rule Knowledge Bases Using Decision Units.- Sound and Complete Propositional Nonmonotonic Logic of Hierarchically-Minimal Models.- Neural Networks and Evolutionary Algorithms.- Artifical Neural Network for Multiprocessor Tasks Scheduling.- Probabilistic Neural Nets in Knowledge Intense Learning Tasks.- Evolutionary Real-Time Optimization System for Ecological Power Control.- Speeding Up Evolution through Learning: LEM.- Evolutionary Search with Erosion of Quality Peaks.- Brain Differently Changes its Algorithms in Parallel Processing of Visual Information.- Handling of Uncertainty.- Discovery of Bayesian Networks From Data with Maintenance of Partially Oriented Graphs.- Visualization in Prediction Based on Grade Correspondence Analysis.- Extension of the HEPAR II Model to Multiple-Disorder Diagnosis.- Evaluation of Bank Transactions Correctness with Method of 2-dimensional Projection of High-Dimensional Fuzzy Membership Functions.- AI for Database Systems.- Consensus-based Methods for Restoring Consistency of Replicated Data.- A Strategy for Partial Evaluation of Views.- Approximate Answers in Databases of Labeled Objects.- Author Index.