In this Project I have build a AI that can play snake game using Deep reinforcement learning based on Deep Q-learning Algorithm .
The Algo It's one of the most populer algo used in Reinforecement learning, it's start by making a random move then he take a reward for each move like 10 for eating an apple and -0.03 for a simpel move and -1 if he lose then wa save the state, action, reward, next state in a memmory that we will use it to correct the nueral.
For the Nueral architecteur I have use Convolutional neural network (cnn) taht take a resized Screenshot of the board-game in shape (10, 10, 1) then he transfere the input to Flatten layer that return the Q value of each action, then we take the action that have the most Q value.
To run the project you should have Python3,Tensorflow, pygame, matplotlib and numpy.
Training the model take between 25k and 30k epoche then he wille be able to eat 6 apple until 13 apple in one epoch. The model will generate h5 file where he wille save his neural value each time he get 3 in scor, to use this file after in test part, and after each 10 epoch the model will generate a graph of score and steps average in image.
To train the model use python3 train.py.
There is also Kaggel_file if you whant to train the model in server like kaggel or google_colab or any others platform.
In testing we will upload the generated file to use it
to test the model use python3 test.py.