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In this lecture, we review the four forces of evolution -- mutation, migration/gene flow, genetic drift, and natural selection -- and the contribution that each one makes to either increasing or decreasing variance in a population over time. 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. We discuss the so-called "drift barrier" -- how the tendency for natural selection to produce higher quality solutions is ultimately limited by genetic drift that dominates when populations have low fitness diversity (low selective pressure) -- and we discuss how this sets up a speed–accuracy tradeoff between mutation (which counteracts drift in a way that does not require more time for convergence but makes it impossible to fine tune solutions) and population size (which can fine tune solutions but requires a longer time to converge to a good solution). Selection operators and evolutionary hyper-parameters should be chosen with these pressures and tradeoffs in mind. Whiteboard notes for this lecture can be found at: https://www.dropbox.com/scl/fi/g4sqsa... This lecture was recorded by Theodore P. Pavlic as part of IEE/CSE 598 (Bio-Inspired AI and Optimization) at Arizona State University.