Heuristic Search GUI with Tkinter

This program is a Python application with a graphical user interface (GUI) that demonstrates two heuristic-based search algorithms:

• Greedy Best First Search
• A* Search

The application uses Tkinter for the GUI, NetworkX for graph structure, and Matplotlib for graph visualization.

Features

• Interactive graph visualization with edge weights and heuristic values for each node.
• Automatic heuristic value calculation using Dijkstra's algorithm.
• Search result comparison between Greedy and A* algorithms.
• Direct visualization of the search path on the graph.

Graph Structure

The graph is static and defined as a Python dictionary like this:

graph = {
    "A": {"B": 2, "C": 3},
    "B": {"A": 2, "D": 4, "E": 5},
    ...
}

Node positions for visualization are manually set using coordinates:

node_positions = {
    "A": (0, 2),
    "B": (1, 3),
    ...
}

How to Run

1. Make sure Python is installed (Python 3.8+ recommended).
2. Install the required dependencies:

pip install matplotlib networkx

3. Run the program (main.py):

python main.py

Algorithms Used

Greedy Best First Search

• Selects the node with the lowest heuristic value.
• Ignores the total travel cost (g(n)).

A* Search

• Uses the formula: f(n) = g(n) + h(n)

  g(n) = total cost so far, h(n) = estimated cost to the goal (heuristic)

• Balances between exploration and exploitation.

Interface Preview

The interface displays:

• Dropdown menus to select the start and goal nodes
• A "Search Route" button to run the algorithms
• Graph visualization with color-coded paths: 🔴 A* Path, 🟢 Greedy Path
• Heuristic values and path results shown below the graph

Dependencies

• tkinter (built-in with Python)
• networkx
• matplotlib
• heapq (built-in with Python)

License

This project is free to use for educational and research purposes.