This project aims to train an artificial neural network to control the cartpole problem using particle swarm optimization.
In order to start the program, open the main.py file. Make sure test is set to True if you would like to see the performance of the neural network.
Otherwise, if you are more interested in training the networks, then choose the hyper parameters as you please and set test to False. After the training is completed, the code will save the best network in a variable called 'best_network.npy' which is a numpy array that can be decoded into a neural network when needed.