In this lecture, we finish our discussion of (a simple version of) the Genetic Algorithm (GA), focusing on different genetic operators for recombination and mutation. We then close our discussion of the GA (for now) emphasizing that selection of these operators and other hyperparameters reflects the delicate balance between natural selection and drift -- with too much selective pressure leading to premature convergence on local suboptima and too little selective pressure leading to drift taking over and a random strategy becoming fixed in the population. At the end of this lecture, we pivot to introducing immunocomputing and artificial immune systems. We will pick up with the AIS discussion next lecture.
Whiteboard notes from this lecture can be found at: https://www.dropbox.com/s/gp0jd6acmtfj8ty/IEE598-Lecture2A-2022-01-27-Beyond_Genetic_Optimization-AIS_and_GenProg.pdf?dl=0
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