🐍🎮 + 🤖 Snake Game with AI Agent

This project implements a classic 🐍 game with an 🤖 agent that uses a 🧠 neural network to make decisions. The 🤖 is trained through a 🧬 genetic algorithm and then tested in the 🎮 environment.

Overview 🔍

The project consists of three main components:

1. SnakeGameLogic: Implements the 🎮 mechanics for the 🐍, including the grid, snake movement, and 🍎 generation.
2. Agent: The 🤖 agent that controls the 🐍, using a simple 🧠 neural network to decide movements based on the current 🎮 state.
3. SnakeGameGUI: Provides a 🎨 graphical interface for visualizing the 🎮 and the agent's actions.

How It Works 🛠️

• The agent receives a perception of the 🌍, which includes ℹ️ about the position of obstacles (⛔️), the direction of the 🐍, and the relative position of the 🍎.
• The agent's decision-making is based on a 🧠 neural network whose weights are optimized through 🧬 genetic algorithms.

Known Issue ⚠️

An issue is currently open due to difficulties encountered when extending the agent's perception to a range of 2️⃣. When the range_vision is set to 2️⃣, the agent tends to perform poorly, resulting in immediate 🎮 termination with a score of 0️⃣. This issue needs further investigation to understand the underlying cause and to improve the agent's performance with an extended perception range.

Running the Game ▶️

To run the 🎮 with the current best-trained 🤖:

python snake_game_gui.py

The 🎮 will start with the 🤖 controlling the 🐍. The objective for the agent is to eat as many 🍎 as possible without colliding with obstacles (⬛️) or itself.

Opening an Issue 📝

To report problems or contribute to the solution of the existing issue regarding the range_vision, please visit the GitHub Issues page and participate in the discussion.

Requirements 📋

• Python 3.x
• Tkinter (for the 🎨 graphical interface)

Future Work 🚀

• Improve the agent's 🧠 neural network to effectively handle an extended perception range.
• Experiment with different 🧠 network architectures to achieve better performance.
• Address the current issue with range_vision of 2️⃣, ensuring stability and improved 🎮 behavior.

Contributing 🤝

Feel free to contribute to the project by opening pull requests or by providing suggestions on the Issues page.