AI-Snake-Game

This is the final project of CPS2232 Data Structure. I use the Q-learning algorithm to play the Snake Game.

Description

This is the snake game. I add one AI player to learn this.

Q-learning:

• Q-table : hashmap: key:apple position;snake position(String); value: up down left right(float).
• State: Q-table.key.
• Reward: distance(-3,0,3), score(80), gameover(-100).
• Action: Q-table.value.
• Environment: --.

Q learning setting:

• greedy 0.3, discount 0.8, learning rate 0.1, action space 4

Document:

• Board: The playing environment for AI or customer player visualization
• Game_1: The playing environment for AI training
• Q_learner: Q learning architecture
• Snake: costomer player environment
• SnakeLearner2: AI player environment
• SnakerLearner3: AI player environment visualization (todo)

Run:

• if you want to play: Snake.java let AI play: SnakeLearner2.java

Acknowledgement

The game structure is borrowed from java-snake-game. Thanks for your sharing!