Lunar-Lander-Deep-Expected-Sarsa

This project is about using deep expected sarsa with tensorflow to solve the lunar lander problem with hyperparameter tuning and result's analysis

These points are important read them please:

all data and models are in results folder
folder tests is just for you if you want to test something
if you want to plot the data, you don't need tensorflow just python and matplotlib
you need TensorFlow 2.3 for it to work

imports
replay buffer class
expected sarsa network
softmax and argmax helper functions
agent class
lunarlander class
loading, parsing plotting helper functions
run experiment function for testing egreedy and softmax
run experiment function for testing batch size and replay steps
run experiment normal run
setting all learning parameters, data and the call for the run experiment function
cell for loading data and defining the loaded variable (run it before trying to plot or test the agent)
cell to compute averages
cell to plot same : plot all data (rewards, loss, episode steps) for each type of tests
cell for choosing best batch size and number of replay steps
cell for choosing best softmax tau and step-size
cell for choosing best e-greedy epsilon and step-size
INFO CELL (IMPORTANT READ IT PLEASE)
cell to load and reconstruct model
cell to plot data of best model
cell to test the agent
thank you :)