stolo93/snake-ai

Reinforcement learning for the game of snake

SNAKE - AI

Reinforcement learning for the game of snake

Rewards:

• Eat food: +10
• Game over: -10
• Else: 0

Actions:

• [1, 0, 0] -> straight
• [0, 1, 0] -> right turn
• [0, 0, 1] -> left turn

Game state description

State (11 values):

[
## Danger position
danger straight, danger right, danger left,

## Snake direction
direction left, direction right,
direction up, direction down,

## Food position
food left, food right,
food up, food down
] 

Model

Feed forward neural network

• input features [11] (state)
• hidden layer
• output [3] action

Loss function

Bellman equation
Simplified: Q = model.predict(state_0)
Q_new = Reward + y*max(Q(state_1))

Mean squared error
loss = (Q_new - Q)^2