python制作小蛇_Snake：贪吃蛇游戏 AI 版，通过算法实现让小蛇通过吃豆

短命女 2022-10-25 14:27 169阅读 0赞

Snake

![68747470733a2f2f7472617669732d63692e6f72672f63687579616e676c69752f736e616b652e7376673f6272616e63683d6d6173746572][]![68747470733a2f2f63692e6170707665796f722e636f6d2f6170692f70726f6a656374732f7374617475732f657736337072317662376565317979692f6272616e63682f6d61737465723f7376673d74727565][]![68747470733a2f2f696d672e736869656c64732e696f2f62616467652f707974686f6e2d332e352b2d626c75652e737667][]

The project focuses on the artificial intelligence of the Snake game. The snake's goal is to eat the food continuously and fill the map with its bodies as soon as possible. Originally, the project was written in C++. It has now been rewritten in Python for a user-friendly GUI and the simplicity in algorithm implementations.

Experiments

We use two metrics to evaluate the performance of an AI:

Average Length: Average length the snake has grown to (max: 64).

Average Steps: Average steps the snake has moved.

Test results (averaged over 1000 episodes):

Solver

Demo (optimal)

Average Length

Average Steps

![solver\_hamilton.gif][solver_hamilton.gif]

63.93

717.83

![solver\_greedy.gif][solver_greedy.gif]

60.15

904.56

DQN

(experimental)

![solver\_dqn.gif][solver_dqn.gif]

24.44

131.69

Installation

Requirements: Python 3.5+ (64-bit) with Tkinter installed.

$ pip3 install -r requirements.txt

\# Use -h for more details

$ python3 run.py \[-h\]

Run unit tests:

$ python3 -m pytest -v

License

See the LICENSE file for license rights and limitations.

[68747470733a2f2f7472617669732d63692e6f72672f63687579616e676c69752f736e616b652e7376673f6272616e63683d6d6173746572]: https://camo.githubusercontent.com/bc03b923977476ea086639ebdd92f0aed02eadb9/68747470733a2f2f7472617669732d63692e6f72672f63687579616e676c69752f736e616b652e7376673f6272616e63683d6d6173746572
[68747470733a2f2f63692e6170707665796f722e636f6d2f6170692f70726f6a656374732f7374617475732f657736337072317662376565317979692f6272616e63682f6d61737465723f7376673d74727565]: https://camo.githubusercontent.com/e34e3b18017087245c2e42aa7ad76bdf8966124f/68747470733a2f2f63692e6170707665796f722e636f6d2f6170692f70726f6a656374732f7374617475732f657736337072317662376565317979692f6272616e63682f6d61737465723f7376673d74727565
[68747470733a2f2f696d672e736869656c64732e696f2f62616467652f707974686f6e2d332e352b2d626c75652e737667]: /images/20221024/eef920a2ccef41248355a842877322bc.png
[solver_hamilton.gif]: https://github.com/chuyangliu/snake/raw/master/docs/images/solver_hamilton.gif
[solver_greedy.gif]: https://github.com/chuyangliu/snake/raw/master/docs/images/solver_greedy.gif
[solver_dqn.gif]: https://github.com/chuyangliu/snake/raw/master/docs/images/solver_dqn.gif