CSE 571 Artificial Intelligence

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

Programs developed for CSCI561 Foundations of Artificial Intelligence course

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.

Implementations of artificial intelligence agents that plays Pac-Man

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

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

Planning Project Implementation for the Udacity Artificial Intelligence Nanodegree Program

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

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.

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

Implementation of UCS algorithm in Python

A visualisation tool for various pathfinding algorithms.

👻 Implementation of intelligent agents for the Pacman game.

Python Implementation of pathfinding algorithms BFS, UCS and A*

UCS(Uniform Cost Search for Directed and Undirected Graph Using Vertice List and Matrix Representation