Due: Wednesday, April 25th.

• Read the papers for the student presentations.
• Begin the final research paper for the course.
• Pick a question to address using your algorithm. The simplest types of questions depend on a parameter of the GA. For example, which of two different types of mutation give the best results. Or two different forms of crossover or selection. You should frame this as a hypothesis, for example: "Our research hypothesis is that using a tournament of size 5 will lead to better fitness values than a tournament size of 3."
• Using the IEEE template from Assignment 9 create a research paper outline. Include sections for the abstract, introduction, methods, results, and conclusion (no background).
• Write a draft introduction for your paper. Very generally what is a genetic algorithm. What is the importance of the component of the genetic algorithm that you are experimenting with? For example, if your experiment focuses on the selection set discuss the importance of selection. Then present the hypothesis you are testing.
• Write a draft methods for your paper. Describe your algorithms, including how selection, crossover, and mutation are done. Describe your experiments. Include a table with the parameters of your algorithm: population size, number of generations, mutation rate (probability of a value mutating), etc.
Turn in: The pdf of your draft research paper.