MazeSolver

This project implements various search algorithms to navigate and solve a maze efficiently. It explores different pathfinding techniques, such as Breadth-First Search (BFS), Depth-First Search (DFS), A (A-star) and Uniform Cost Search (UCS), to determine the optimal route from a start position to a goal within a maze environment.

Download This Repository

To download this repository, click on the Code button at the top of this page and select Download ZIP or use the following command:

git clone https://github.com/your-username/your-repo-name.git

Steps to Run the Code

Windows

Step 1: Make sure Python is installed in the system

Step 2: If you wish to continue without creating a virtual environment and run the code on the terminal, install the requirements using:

pip install -r requirements.txt

Step 3: If you wish to create a virtual environment, follow these steps:

# a. Create a virtual environment
python -m venv venv

# b. Activate the virtual environment
.\venv\Scripts\activate

# c. Install the requirements
pip install -r requirements.txt

Step 4: Ensure all the packages are installed using:

pip list

Step 5: To run the main code, use:

python main.py

Linux

Step 1: Make sure Python is installed in the system

Step 2: If you wish to continue without creating a virtual environment and run the code on the terminal, install the requirements using:

pip install -r requirements.txt

Step 3: If you wish to create a virtual environment, follow these steps:

# a. Create a virtual environment
python -m venv venv

# b. Activate the virtual environment
source venv/bin/activate

# c. Install the requirements
pip install -r requirements.txt

Step 4: Ensure all the packages are installed using:

pip list

Step 5: To run the main code, use:

python main.py