A PyTorch Toolbox for creating adversarial examples that fool neural networks.

Code for the paper "Skynet: A Top Deep RL Agent in the Inaugural Pommerman Team Competition"

Multiplayer snake AI

Automated Testing Framework for CARLA Simulator [ITSC 2022]

Halma game with an AI player, move validation, and dynamic board sizing

🤖 Chess AI using the minimax algorithm with alpha-beta pruning.

Solutions to Pacman AI Multi-Agent Search problems

An AI Agent based on Alpha Beta Pruning for the Tic Tac Toe Game.

In this project, you will design agents for the classic version of Pacman, including ghosts. Along the way, you will implement both minimax and expectimax search and try your hand at evaluation function design.

A sophisticated AI-powered debate platform that integrates Large Language Models with Genetic Algorithms and Adversarial Search to create a dynamic and adaptive debating experience.

The phase 2 of my AI project, which is adversarial search in Pacman game for reaching the best utility and avoiding ghosts. Minimax with alpha-beta pruning and Expectimax is implemented.

This github repository contains the official code for the papers, "Robustness Assessment for Adversarial Machine Learning: Problems, Solutions and a Survey of Current Neural Networks and Defenses" and "One Pixel Attack for Fooling Deep Neural Networks"

Some Artificial Intelligence & Machine Learning algorithms

Create an agent to intelligently play the 2048-puzzle game

Artificial Intelligence Projects

This repository is dedicated to the study and implementation of Artificial Intelligence Techniques (AIT). It covers core AI concepts such as problem-solving with search, uninformed and informed strategies, adversarial game playing, knowledge representation, and reasoning

Creating a player for the game of quarto based on GA, RL, MinMax and other strategies

My code and report of Udacity AI nanodegree project3 Adversarial Game Playing Agent

Search, Knowledge, Uncertainty, Optimization, Learning, Neural Networks and Language.

Play Connect4 against an intelligent AI agent using Minimax Algorithm with and without Pruning