A visualizer for the core search algorithms used in AI and game development. Special thanks to Amit Patel and his cool tutorials for providing me with the inspiration. #MadeWithUnity

This repository contains implementation of different AI algorithms, based on the 4th edition of amazing AI Book, Artificial Intelligence A Modern Approach

CSE 571 Artificial Intelligence

GraphLab is an application that shows visually how several graph algorithms work

Find the shortest route using A* algorithm and graphs (Route Planner application)

this project combines various AI algorithms to provide visualization and functionality for search algorithms, a game (CONNECT4) using min-max algorithms, and a Constraint Satisfaction Problem (CSP) solver. This toolbox aims to provide a comprehensive understanding of these AI techniques through interactive visualizations and practical examples.

A fine-tuned visual implementation of Informed and Uninformed Search Algorithms such as Breadth First Search, Depth First Search, Uniform Cost Search, A* Search, Greedy First Search

Visualization for multiple searching algorithms.

Implement Algorithms For Graph Search (like A*) & Local Search (like hill climbing algorithms) & Genetics

Uniform Cost Search implementation for Artificial Intelligence course

Desktop app for visualizing graph search algorithms

DFS / BFS / IDS / UCS / Bi-directional / A* / IDA* / SMA* / ...

Robot that cleans room from dirts. Finds the optimum path eventually. Same algorithms are applied as in finding path to escape a maze.

Implementations of artificial intelligence agents that plays Pac-Man

CIT-316 (Artificial Intelligence Sessional)

All Artificial Intelligence Search algorithms. Depth first search, Breadth first search, uniform cost search, Greedy search, A star search, Minimax and Alpha beta pruning. Implemented in Python 3.

Programs developed for CSCI561 Foundations of Artificial Intelligence course

Solves Sokoban Puzzles using A* search, UCS algorithms and heuristic functions

Planning Project Implementation for the Udacity Artificial Intelligence Nanodegree Program

Program that searches for the shortest route using the 'Uniform Cost Search' algorithm by consulting a map of the province of Santo Domingo extracted from OpenStreetMap.

java, discrete map search, uniform cost search algorithm

Calculating the shortest path between two nodes with the Uniform Cost Search algorithm.

Implementation of algorithms to solve N-Puzzles in haskell

Attempts to solve the 8-Puzzle by using various heuristic search methods. Written in Python.

The algorithm determines the least cost path from the start location to goal location

Path finding algorithms to find a path between pixels of images representing geographical features. Shows an OpenCV image output of traversal.

A structured collection of fundamental Artificial Intelligence Search Algorithms implemented in Python with Jupyter Notebooks — complete with pseudocode, working examples, and visual explanations.

Project | Artificial Intelligence Tournament

classical search algorithms are used in AI | AI course - Fall 2018

A project for Fundamental of Optimization class at HUST, Winter 2022