https://github.com/vaneeza-7/graph-optimization-problem-using-uninformed-search

Calculating the minimum cost and optimal path for a graph using bfs, dfs, and ucs in Artificial Intelligence
https://github.com/vaneeza-7/graph-optimization-problem-using-uninformed-search

artificial-intelligence artificial-intelligence-algorithms bfs dfs graph minimum-cost networkx optimal-path ucs

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Calculating the minimum cost and optimal path for a graph using bfs, dfs, and ucs in Artificial Intelligence

• Host: GitHub
• URL: https://github.com/vaneeza-7/graph-optimization-problem-using-uninformed-search
• Owner: Vaneeza-7
• License: mit
• Created: 2024-02-28T18:42:33.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2024-06-25T19:42:51.000Z (almost 2 years ago)
• Last Synced: 2025-01-07T15:44:33.691Z (over 1 year ago)
• Topics: artificial-intelligence, artificial-intelligence-algorithms, bfs, dfs, graph, minimum-cost, networkx, optimal-path, ucs
• Language: Jupyter Notebook
• Homepage:
• Size: 148 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Graph Optimized Path Finding

Calculating the minimum cost and optimal path for a graph using BFS, DFS, and UCS in Artificial Intelligence.

Assignment @ Artificial Intelligence

## Algorithms

- **Breadth-First Search (BFS)**: Explores all possible paths level by level, ensuring the shortest path in an unweighted graph.

- **Depth-First Search (DFS)**: Explores paths by going as deep as possible, useful for exploring all possible paths in a graph.

- **Uniform Cost Search (UCS)**: Finds the least cost path in a weighted graph, expanding the least cost node first.

## License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.