Evolving rule based models

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The concept behind this book has evolved during its preparation, with some results emerging alongside the writing process. This is due to the rapid updates in research and the lack of a strong, unchallenged theoretical foundation in the field. Additionally, the increasing pace of innovation, competition, and demand across various industries—ranging from biotechnology to civil engineering, market forecasting, civil aviation, robotics, and e-commerce—calls for more customized solutions that leverage consumer behavior insights. This has led to the emergence of a highly interdisciplinary and innovative field focused on designing intelligent, self-adapting systems and machines. This area sits at the intersection of control theory, artificial and computational intelligence, and various engineering disciplines, drawing heavily from biology and life sciences. Commonly referred to as intelligent control, soft computing, or intelligent technology, it encompasses new branches like intelligent agents, data fusion, and knowledge extraction. The core aim is to enhance classical control theory, developing more adequate, flexible, and adaptive models and control algorithms.