Phyllotaxis and More on Genetic Algorithms

The course covers the following learning outcomes and goals: Algorithmic Botany Coding Challenge on Phyllotaxis, Improving the Fitness function in Genetic Algorithms, Pool Selection in Genetic Algorithms, Interactive Selection in Genetic Algorithms, and Continuous Evolutionary Systems in Genetic Algorithms. Individual skills and tools taught include coding challenges, algorithmic problem-solving, implementing fitness functions, pool selection techniques, interactive selection methods, and ecosystem simulation in the context of Genetic Algorithms. The teaching method of the course involves live-coding sessions, demonstrations, and explanations by the instructor. The intended audience for this course includes individuals interested in algorithmic botany, genetic algorithms, coding challenges, and evolutionary systems.