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)

Visualization for multiple searching algorithms.

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

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

Uniform Cost Search implementation for Artificial Intelligence course

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

Desktop app for visualizing graph search algorithms

Programs developed for CSCI561 Foundations of Artificial Intelligence course

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.

Planning Project Implementation for the Udacity Artificial Intelligence Nanodegree Program

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

Implementations of artificial intelligence agents that plays Pac-Man

java, discrete map search, uniform cost search algorithm

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.

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