Artificial immune systems

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This comprehensive exploration delves into various frameworks and applications of artificial immune systems (AIS). It begins with conceptual and theoretical foundations, presenting innovative works such as an interactive audiovisual artwork utilizing an artificial immune system and a comparative study of clonal selection algorithms. The investigation extends to alternative shapes for recognition regions and a generic framework for population-based algorithms on multiple FPGAs. Key topics include dynamic routing frameworks, biomolecular immune-computer simulations, and the impact of gene libraries on AIS development. The text also discusses the nuances of innate immunity, innovative algorithms inspired by immune responses, and mathematical modeling of immune suppression. It evaluates immunological memory theories through large-scale simulations and presents a quaternion model of artificial immune response. Various optimization strategies, including a modified AIS for multiobjective problems and spam detection algorithms, are examined. Additional applications feature adaptive clustering algorithms, quantum-inspired methods, and peer-to-peer strategies for blacklisting. The work highlights the medical applications of AIS in diagnosing diseases and emphasizes the potential of immune-inspired approaches in diverse fields, showcasing the evolution and future of artificial immune systems.