Generate the data for A.I. to play the Snake game

Question

I would like to generate some data (position of the snake, available moves, distance from the food...) to create a neural network model so that it can be trained on the data to play the snake game. However, I don't know how to do that. My current ideas are:

• Play manually (by myself) the game for many iterations and store the data (drawback: I should play the game a lot of times).
• Make the snake do some random movements track and track their outcomes.
• Play the snake with depth-fist search or similar algorithms many times and store the data.

Can you suggest to me some other method or should I choose from one of those? Which one in that case?

PS I don't know if it is the right place to ask such a question. However, I don't know whom/where to ask such a question hence, I am here.

Answer 1

If using a neural network, start simple. Think inputs and outputs and keep them simple too.

Inputs:

• How many squares to the left of the head are free
• How many squares to the right of the head are free
• How many squares forward of the head are free
• Relative position of next food left/right
• Relative position of next food forward/back
• Length of snake

keep inputs normalized to the minimum and maximum possible values to keep inputs in range -1.0 to 1.0

Outputs:

• Turn Left
• Turn Right
• Straight Ahead

(choose the output with highest activation)

Next problem is training. Typical application might be use a genetic algorithm for all the weights of the above neural network. This randomizes and tests new versions of the neural network every life. After X attempts, create a new evolution and repeat to improve. This is pretty much doing random moves automatically (your second choice)

Next problem is fitness for training. How do you know which neural network is better? Well you could simply use the length of the snake as a fitness factor - the longer the snake, the better and more 'fit'