In this lecture, we review the two major evolutionary forces of natural selection and genetic drift and how they tend to reduce variance in a population over time. We then introduce mutation and recombination, which add diversity to populations. So a more complete picture of evolution is a tense combination of these forces, each of them leading to different kinds of effects on the distribution of alleles (strategies) in a population. This allows us to introduce a concrete example of an evolutionary algorithm -- the genetic algorithm (GA). We start to define its key components and sequence of operation. In Part 2 (the next lecture), we will go into detail about the selection, mutation, and recombination "genetic operators."
Whiteboard notes for this lecture are archived at: https://www.dropbox.com/s/arz17hcpiw4wacy/IEE598-Lecture1D-2022-01-20-The_Genetic_Algorithm_and_its_Implementation-Part_1.pdf?dl=0
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