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Titlebook: Applications of Evolutionary Computation; 26th European Confer João Correia,Stephen Smith,Raneem Qaddoura Conference proceedings 2023 The E

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Abnormal Cardiac Electrical Activityoaches have proved promising, with attention turning more recently to evolving repertoires of diverse behaviours that can be used to compose heterogeneous swarms or mitigate against faults. Here we extend existing work by combining a Quality-Diversity algorithm (MAP-Elites) with a Genetic-Programmin
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Activation Induced Cell Death (AICD)odes stochastically. Several detectors are unable to detect this malware family because of how quickly they obfuscate their code. It has also been shown that Machine learning (ML) models are not robust to these attacks due to the insufficient data to train these models resulting from the constant co
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Abnormal Cardiac Electrical Activityeased tremendously in recent decades. While these applications provide numerous benefits to our daily lives, they also pose a great potential risk in terms of security. One of the reasons for this is that devices in IoT-based networks are highly resource constrained and interconnected over lossy lin
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https://doi.org/10.1007/978-3-540-29807-6s an iteration of steps that stops when the engineer is happy with both the cost and maintaining the structural constraints of the solution. The problem’s difficulty arises from the fact that changing a variable may affect other variables, meaning that they are not independent, suggesting that we ar
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Acquired Immune Deficiency Syndrome (AIDS)n the literature to organize their storage in a structured way. However, the full potential of these formal methods to capture our domain knowledge has yet to be demonstrated. In this work, we evaluate a performance prediction model built on top of the extension of the recently proposed OPTION ontol
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https://doi.org/10.1007/978-3-031-30229-9Artificial Intelligence; Machine Learning; Evolutionary optimization; Evolutionary Computation; Meta-heu
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