Search-Optimization-Algorithms

A complete Python implementation of the most important Artificial Intelligence search and optimization algorithms, with practical examples and comparison.

Included Algorithms

• Breadth-First Search (BFS)
• Depth-First Search (DFS)
• Uniform Cost Search (UCS)
• Greedy Best-First Search
• A* Search
• Genetic Algorithm (GA)

Each algorithm includes:

• Clean implementation
• Iterative and/or recursive versions
• Real-world applications (pathfinding, routing, optimization, puzzles)

Project Structure

AI_Algorithms_Code.py        # Full implementations + demo runner
AI_Algorithms_Comparison.docx # Theory + detailed comparison
README.md

How to Run

Make sure you have Python 3.8+ installed:

python AI_Algorithms_Code.py

The script runs all algorithms with example data and prints results.

Purpose

This repository is designed for:

• AI coursework
• Interview preparation
• Understanding search strategies
• Learning heuristic and evolutionary optimization

A compact, practical reference for core AI algorithms.