Since we are not going to have a full fifth homework for the class,
we're going to offer this set of questions as extra credit for those
of you who want it. You don't have to do this homework, but if you
want a few extra points, and you have the time, then here it is.
Assignment
Design and implement a genetic algorithm to solve the grid world
problem from homework 4 part 7. Be
careful to describe the representation you choose for your
individuals, exactly how your three operators (selection, crossover,
and mutation) modify these individuals, and your fitness function.
Run a set of experiments to see how varying the population size,
mutation rate, and other parameters affects the quality of the final
solution, and the time taken to reach this solution. Report on these
experiments, showing the learned policies, and compare them to those
learned by Q-learning in homework 4. If you did not attempt this
question in homework 4, you can use the results of another student as
a comparison (but you cannot use any of their code in your GA
implementation). [30 points].
What to Hand In
Write a report on your design, implementation, and experiments, and
email it to the instructor by
the deadline. Include an electronic copy of your code.