AI_Lab — State Space Search & Classic AI Examples

A small collection of AI example programs (C, Prolog and search algorithms) demonstrating state-space search techniques, heuristics, and classic planning problems.

Contents of this repository include implementations and sample inputs for puzzles and problems such as the sliding-tile puzzle (A*), Tower of Hanoi, N-Queens, Missionaries & Cannibals, and simple neural network demo for the IRIS dataset.

Table of contents

• Demo (playable video)
• Quick overview
• Repository structure
• Build & run (example)

Demo (playable video)

Watch the A* algorithm solve the N-puzzle problem in action:

Note: If the video doesn't play directly on GitHub's web interface, you can download it using the link above or view the repository via GitHub Pages.

Quick overview

• Language: primarily C and Prolog
• Topics: state-space search, A* heuristic search, BFS, classic planning problems, simple neural network example for IRIS dataset

Repository structure

• Neural Network done in C/ — small C neural network and IRIS dataset sample
• Prolog Programs/ — a set of classic Prolog problems and solutions
• State Space Search/ — C implementations for N-Puzzle-Problem and search techniques

Build & run (example)

General steps for compiling C examples (example uses the sliding-puzzle file name, adjust to the file you want):

1. Open a terminal and change to the folder containing the C file you want to run. Example:

cd "State Space Search"
gcc -o sliding "Sliding-puzzle Proble using A-star algorithm.c" -O2
./sliding

Notes:

• Filenames in this repo sometimes contain spaces; wrap them in quotes when using the shell.
• You only need a C compiler (e.g., gcc) for the C programs.