Advances in Machine Learning II: Dedicated to the memory of Professor Ryszard S. Michalski (Studies in Computational Intelligence (263))

This is the second volume of a large two-volume editorial project we wish to dedicate to the memory of the late Professor Ryszard S. Michalski who passed away in 2007. He was one of the fathers of machine learning, an exciting and relevant, both from the practical and theoretical points of view, area in modern computer science and information technology. His research career started in the mid-1960s in Poland, in the Institute of Automation, Polish Academy of Sciences in Warsaw, Poland. He left for the USA in 1970, and since then had worked there at various universities, notably, at the University of Illinois at Urbana – Champaign and finally, until his untimely death, at George Mason University. We, the editors, had been lucky to be able to meet and collaborate with Ryszard for years, indeed some of us knew him when he was still in Poland. After he started working in the USA, he was a frequent visitor to Poland, taking part at many conferences until his death. We had also witnessed with a great personal pleasure honors and awards he had received over the years, notably when some years ago he was elected Foreign Member of the Polish Academy of Sciences among some top scientists and scholars from all over the world, including Nobel prize winners. Professor Michalski’s research results influenced very strongly the development of machine learning, data mining, and related areas. Also, he inspired many established and younger scholars and scientists all over the world. We feel very happy that so many top scientists from all over the world agreed to pay the last tribute to Professor Michalski by writing papers in their areas of research. These papers will constitute the most appropriate tribute to Professor Michalski, a devoted scholar and researcher. Moreover, we believe that they will inspire many newcomers and younger researchers in the area of broadly perceived machine learning, data analysis and data mining. The papers included in the two volumes, Machine Learning I and Machine Learning II, cover diverse topics, and various aspects of the fields involved. For convenience of the potential readers, we will now briefly summarize the contents of the particular chapters. Front Matter....Pages - Front Matter....Pages 1-1 Knowledge-Oriented and Distributed Unsupervised Learning for Concept Elicitation....Pages 3-21 Toward Interactive Computations: A Rough-Granular Approach....Pages 23-42 Data Privacy: From Technology to Economics....Pages 43-74 Adapting to Human Gamers Using Coevolution....Pages 75-100 Wisdom of Crowds in the Prisoner’s Dilemma Context....Pages 101-118 Front Matter....Pages 119-119 Towards Multistrategic Statistical Relational Learning....Pages 121-142 About Knowledge and Inference in Logical and Relational Learning....Pages 143-153 Two Examples of Computational Creativity: ILP Multiple Predicate Synthesis and the ‘Assets’ in Theorem Proving....Pages 155-173 Logical Aspects of the Measures of Interestingness of Association Rules....Pages 175-203 Front Matter....Pages 205-205 Clustering the Web 2.0....Pages 207-223 Induction in Multi-Label Text Classification Domains....Pages 225-244 Cluster-Lift Method for Mapping Research Activities over a Concept Tree....Pages 245-257 On Concise Representations of Frequent Patterns Admitting Negation....Pages 259-289 Front Matter....Pages 291-291 A System to Detect Inconsistencies between a Domain Expert’s Different Perspectives on (Classification) Tasks....Pages 293-314 The Dynamics of Multiagent Q -Learning in Commodity Market Resource Allocation....Pages 315-349 Simple Algorithms for Frequent Item Set Mining....Pages 351-369 Monte Carlo Feature Selection and Interdependency Discovery in Supervised Classification....Pages 371-385 Machine Learning Methods in Automatic Image Annotation....Pages 387-411 Front Matter....Pages 413-413 Integrative Probabilistic Evolving Spiking Neural Networks Utilising Quantum Inspired Evolutionary Algorithm: A Computational Framework....Pages 415-425 Machine Learning in Vector Models of Neural Networks....Pages 427-443 Front Matter....Pages 413-413 Nature Inspired Multi-Swarm Heuristics for Multi-Knowledge Extraction....Pages 445-466 Discovering Data Structures Using Meta-learning, Visualization and Constructive Neural Networks....Pages 467-484 Neural Network and Artificial Immune Systems for Malware and Network Intrusion Detection....Pages 485-513 Immunocomputing for Speaker Recognition....Pages 515-529 Back Matter....Pages - Annotation This is the second volume of a large two-volume editorial project we wish to dedicate to the memory of the late Professor Ryszard S. Michalski who passed away in 2007. He was one of the fathers of machine learning, an exciting and relevant, both from the practical and theoretical points of view, area in modern computer science and information technology. His research career started in the mid-1960s in Poland, in the Institute of Automation, Polish Academy of Sciences in Warsaw, Poland. He left for the USA in 1970, and since then had worked there at various universities, notably, at the University of Illinois at Urbana €“ Champaign and finally, until his untimely death, at George Mason University. We, the editors, had been lucky to be able to meet and collaborate with Ryszard for years, indeed some of us knew him when he was still in Poland. After he started working in the USA, he was a frequent visitor to Poland, taking part at many conferences until his death. We had also witnessed with a great personal pleasure honors and awards he had received over the years, notably when some years ago he was elected Foreign Member of the Polish Academy of Sciences among some top scientists and scholars from all over the world, including Nobel prize winners.Professor Michalski€™s research results influenced very strongly the development of machine learning, data mining, and related areas. Also, he inspired many established and younger scholars and scientists all over the world.We feel very happy that so many top scientists from all over the world agreed to pay the last tribute to Professor Michalski by writing papers in their areas of research. These papers will constitute the most appropriate tribute to Professor Michalski, a devoted scholar and researcher. Moreover, we believe that they will inspire many newcomers and younger researchers in the area of broadly perceived machine learning, data analysis and data mining.The papers included in the two volumes, Machine Learning I and Machine Learning II, cover diverse topics, and various aspects of the fields involved. For convenience of the potential readers, we will now briefly summarize the contents of the particular chapters "Intelligent engineering systems try to replicate fundamental abilities of humans and nature in order to achieve sufficient progress in solving complex problems. In an ideal case multi-disciplinary applications of different modern engineering fields can result in synergistic effects. Information technology and computer modeling are the underlying tools that play a major role at any stages of developing intelligent systems. Chapters in the present volume have been written by eminent scientists from different parts of the world, dealing with challenging problems for efficient modeling of intelligent systems. The reader can find different characteristics and methodologies of computational intelligence with real life applications. Various facets of intelligent engineering and information technology are addressed. Starting with theoretical issues from pseudo-analysis to parametric classes of digital fuzzy conjunctions for hardware implementation of fuzzy systems, diverse aspects of control including quantum as well as fuzzy control and hybrid approaches, intelligent robotics dealing with mobile and autonomous robots and new trends, approaches and results on information technology, machines, materials and manufacturing, and issues of intelligent systems and complex processes are covered."--Publisher's website 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. This book presents the state of the art of computational intelligence ion engineering. It offers challenging problems for efficient modeling of intelligent systems and details different methodologies of computational intelligence with real life applications.