https://github.com/lpapailiou/snake
WIP - A snake game in java, allowing to play manually and challenge different bots.
https://github.com/lpapailiou/snake
ai artificial-intelligence artificial-intelligence-algorithms hamilton hamiltonian hamiltonian-cycles hamiltonian-monte-carlo java java-8 javafx javafx-application javafx-desktop-apps javafx-gui snake snake-game
Last synced: 6 months ago
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WIP - A snake game in java, allowing to play manually and challenge different bots.
- Host: GitHub
- URL: https://github.com/lpapailiou/snake
- Owner: lpapailiou
- Created: 2020-07-27T19:58:15.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2022-11-16T01:45:28.000Z (almost 3 years ago)
- Last Synced: 2025-02-04T15:50:26.216Z (8 months ago)
- Topics: ai, artificial-intelligence, artificial-intelligence-algorithms, hamilton, hamiltonian, hamiltonian-cycles, hamiltonian-monte-carlo, java, java-8, javafx, javafx-application, javafx-desktop-apps, javafx-gui, snake, snake-game
- Language: Java
- Homepage:
- Size: 256 KB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
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README
# WIP - snake
A __snake__ game, with multiple ai algorithms.
Currently, this project is used to test the [neuralnetwork library](https://github.com/lpapailiou/neuralnetwork).
## Table of Contents
1. [About the game](#about-the-game)
2. [Implemented AI](#implemented-ai)
2.1 [Hamiltonian cycle](#hamiltonian-cycle)
2.2 [A* algorithm](#a-algorithm)
3. [Purpose of this project](#purpose-of-this-project)
4. [Project structure](#project-structure)
5. [How to get it](#how-to-get-it)
## About the game
The game offers a manual mode, which is controlled by the keyboard.
* __arrow left__, __arrow right__, __arrow up__, __arrow down__: will switch to this direction for the next snake move(s).
Alternatively, a bot can overtake the moves. Currently, the gui does not allow choosing between different modes.
## Implemented AI
### Hamiltonian cycle
One of the most known algorithms to solve snake with an ai is to implement a hamiltonian cycle as base path. A hamiltonian
cycle is basically a circular path, with runs through every node (here 'cell') of a graph (here 'game panel').
This algorithm only works though, if the game panel has an even number of cells (e.g. a 25x25 panel will fail as one cell will
never be included in the path).
Example of a such base path:
The snake can strictly follow this path. As a result, it will never run into its own body or a wall.
If the snake is small, this may result in unreasonable long paths, thus an inefficient timing. To solve this, path sections can
be skipped in earlier stages. The snake will remain basically on the base path, which will avoid that a whole new path
has to be calculated after a goodie is reached.
But - how to find the best shortcut efficiently?
### A* algoritm
A good option to find the best shortcut fast is offered by the A*-algorithm (which is used also in map software to calculate the shortest routes).
This algorithm will first build up a graph, then - based on weight and distance - calculate the shortest possible shortcut.
In the current implementation, the graph is build for the current hamilton path section to the next goodie. Meaning: the snake will
still stay on the hamiltonian cycle.
## Purpose of this project
This project ist mainly for playing around with Java.
## Project structure
* ``ai`` here, all ai related code is in
* ``application`` this package contains the main method (in ``Driver.java``), and gui related code
* ``game`` here most part of the game logic is in
* ``util`` helper classes
## How to get it
Clone the repository with:
git clone https://github.com/lpapailiou/snake your-target-path
For further help, click [here](https://gist.github.com/lpapailiou/d4d63338ccb1413363970ac571aa71c9).