AI learns how to play snake game

The solution uses Deep Reinforcement Learning (Q-learning) approach.

Result

Repository contains trained network (after 1000 iterations)

Visualisation

Input

1. is wall/tail directly up front
2. is wall/tail directly on the right side
3. is wall/tail directly on the left side
4. is snack ahead (no matter how far)
5. is snack on the right (no matter how far)
6. is snack on the left (no matter how far)

Output

1. do nothing (keep going on current direction)
2. turn right
3. turn left

Reward table

• +1 for finding snack
• -1 for hitting wall/tail

Network settings

Param	Value	Info
LEARNING_RATE	0.001
GAMMA	0.95	Discount rate
EPSILON	1.0	Exploration rate
EPSILON_DECAY	0.995
EPSILON_MIN	0.01
MEMORY	2000	Experience replay
MINI_BATCH	32