Assignment9/10

Assignment9: develop a random neural network and get the robot to move
with the touch sensors firing correctly

Assignment 10: Connect the bullet demo to the python hill climber and
evolve the robot to move with high fitness into the screen. The bullet
script terminates at 1000 time steps and sends a single fitness value
to the python script, which perturbs either the previous parent
synaptic weights or the child’s synaptic weights, then sends the file
to the bullet script to test that generations fitness versus the new
parent
Final Project Report 2

Moved the legs to the x-left and x-right sides exclusively and evolved
the robot for a high fitness into the screen
Assignment 10.3

Added two legs, with four body parts and 4 motors/hinges, as well as
two touch sensors, to my robot to create a hexapod. Evolved the robot
for 15 or so generations to achieve high fitness moving into the
screen. Cleaned up the code significantly— my next move is to clean the
code up for my other two robots to make working on them this final week
much easier