🚇 London Tube AI Search – DFS, BFS, UCS, Heuristics

This project applies search algorithms to the London Underground map to find optimal routes based on time and zone.

🔍 Features

• Implements DFS, BFS, UCS, and Zone-Based Heuristic Search
• Graph state representation with cost and zone metadata
• Extended cost model for line changes
• Compares performance and optimality

📂 Files

• undirected_map_final_vickshan_vicknakumaran.ipynb – Main implementation notebook
• tubedata.csv – Tube map with station-to-station data

📊 Sample Result

Route: New Cross Gate → Stepney Green

Algorithm	Time (min)	Nodes Explored
DFS	27	35
BFS	12	8
UCS	14	19

🏫 Module Info

• Year: 2024
• University: Queen Mary University of London
• Author: Vickshan Vicknakumaran

🧠 How to Run

Open the notebook in Jupyter, ensure tubedata.csv is in the same directory, and run cells in order.

📜 License

For academic and research use only.