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[To be updated]
This is the code for my Graph Coloring Exploration Project, which was my Artificial Intelligence course project at Amirkabir University of Technology (aka AUT or Tehran Polytechnic). My implementations not only return the adjacancy matrix of the graph, but also visualize the colored result graph.
Goal
The goal of this project was to implement and compare some of the famous Heuristic algorithms and AI approaches to the Graph Coloring problem.
[NEW!]
I wrote a Python script to extract the adjacency matrix of graphs in .col and .col.b format from here.
A brief description of the files:
- AIproject - Back Tracking-DFS.py: An exact approach to solve the graph coloring problem using a back tracking algorithm
- AIproject - HC.py: An approximation of the coloring using Hill Climbing algorithm
- AIproject - IDS.py: An implementation using the Iterative-deepening search algorithm
- AIproject - Learning Model (2).ipynb: A naive approach to predict the chromatic number using linear regression
- AIproject - SA.py: An approximation of the coloring using Simulated Annealing algorithm
- data.csv: Contains the adjacancy matrix of some famous graphs from here
- extract_adj_matrix.py: The code that extracted the adjacancy matrix of graphs from .col and .col.b format into a .csv file
