🤖 AI-Codes

This repository contains a variety of Artificial Intelligence (AI) algorithm implementations in Python using Jupyter Notebooks. These cover classic AI topics such as search algorithms, optimization, and problem-solving strategies.

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🧠 Contents

🔍 Search Algorithms

• Uniform Cost Search for Optimal Path.ipynb
• Search for Treasure using the Best-First Search.ipynb
• Maze Solver using BFS and DFS.ipynb
• Route Finder Using Bi-Directional BFS & DFS.ipynb

🎮 Game & Puzzle Solvers

• Game AI Using Search Algorithms.ipynb
• Water_jug.ipynb (Water Jug Problem solver using AI search)
• Untitled.ipynb (Possibly a draft or demo - please rename if used)

🧬 Optimization Algorithms

• Implementation of Genetic Algorithm (GA) for Optimization.ipynb

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✅ Features

• Core AI algorithms implemented in Python
• Hands-on illustrations with step-by-step logic
• Ideal for learning and academic submissions
• Visual and interactive notebooks for better understanding

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🚀 Getting Started

To run these notebooks locally:

1. Clone the repository:

   git clone https://github.com/your-username/AI-Codes.git
   cd AI-Codes

2. Open the notebooks:

   jupyter notebook

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📦 Requirements

Install the required packages using pip if not already available:

pip install numpy matplotlib notebook

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🧑‍💻 Author

Made by Rohan1188

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📄 License

This project is licensed under the MIT License.