Advances in Machine Learning II Dedicated to the memory of Professor Ryszard S. Michalski

Professor Richard S. Michalski passed away on September 20, 2007. Once we learned about his untimely death we immediately realized that we would no longer have with us a truly exceptional scholar and researcher who for several decades had been inf- encing the work of numerous scientists all over the world - not only in his area of exp- tise, notably machine learning, but also in the broadly understood areas of data analysis, data mining, knowledge discovery and many others. In fact, his influence was even much broader due to his creative vision, integrity, scientific excellence and excepti- ally wide intellectual horizons which extended to history, political science and arts. Professor Michalski’s death was a particularly deep loss to the whole Polish sci- tific community and the Polish Academy of Sciences in particular. After graduation, he began his research career at the Institute of Automatic Control, Polish Academy of Science in Warsaw. In 1970 he left his native country and hold various prestigious positions at top US universities. His research gained impetus and he soon established himself as a world authority in his areas of interest – notably, he was widely cons- ered a father of machine learning.

General Issues.- Knowledge-Oriented and Distributed Unsupervised Learning for Concept Elicitation.- Toward Interactive Computations: A Rough-Granular Approach.- Data Privacy: From Technology to Economics.- Adapting to Human Gamers Using Coevolution.- Wisdom of Crowds in the Prisoner’s Dilemma Context.- Logical and Relational Learning, and Beyond.- Towards Multistrategic Statistical Relational Learning.- About Knowledge and Inference in Logical and Relational Learning.- Two Examples of Computational Creativity: ILP Multiple Predicate Synthesis and the ‘Assets’ in Theorem Proving.- Logical Aspects of the Measures of Interestingness of Association Rules.- Text and Web Mining.- Clustering the Web 2.0.- Induction in Multi-Label Text Classification Domains.- Cluster-Lift Method for Mapping Research Activities over a Concept Tree.- On Concise Representations of Frequent Patterns Admitting Negation.- Classification and Beyond.- A System to Detect Inconsistencies between a Domain Expert’s Different Perspectives on (Classification) Tasks.- The Dynamics of Multiagent Q-Learning in Commodity Market Resource Allocation.- Simple Algorithms for Frequent Item Set Mining.- Monte Carlo Feature Selection and Interdependency Discovery in Supervised Classification.- Machine Learning Methods in Automatic Image Annotation.- Neural Networks and Other Nature Inspired Approaches.- Integrative Probabilistic Evolving Spiking Neural Networks Utilising Quantum Inspired Evolutionary Algorithm: A Computational Framework.- Machine Learning in Vector Models of Neural Networks.- Nature Inspired Multi-Swarm Heuristics for Multi-Knowledge Extraction.- Discovering Data Structures Using Meta-learning, Visualization and Constructive Neural Networks.- Neural Network and Artificial Immune Systems forMalware and Network Intrusion Detection.- Immunocomputing for Speaker Recognition.