Collection of Notebooks in Google Colab directly usable for study activities

Minimax with/without alpha-beta pruning and heuristic evaluation function.

Series of 11 works, covering: State-Space Representations, Search, Adversarial Search, Logic, Automated Reasoning, Reasoning with Uncertainty and Vagueness and Machine Learning

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

TicTacToe with AI [Beginner's Project]

A Tic Tac Toe game to vs. AI computer player trying to win within (or without) a limited decision making time. Adversarial Search Algorithms (minmax, Alpha-Beta, MonteCarlo)

This Python-based Tic Tac Toe game features an AI opponent that uses adversarial search with the minimax algorithm and alpha-beta pruning. Experience strategic gameplay as the AI makes optimal moves to challenge players, ensuring a competitive and engaging experience.

Code accompanying the paper "Lookahead Pathology in Monte Carlo Tree Search" (ICAPS, 2024)

DTU course 02180 Introduction to Artificial Intelligence, Spring 2024

some informed, uninformed, adversarial and local searches

An adversarial agent for playing Tic Tac Toe, offering users the option to choose board size and difficulty level. Utilizes various search algorithms including, but not limited to; Alpha-Beta Pruning, Expectimax, and Minimax. The project provides an interactive interface where users can play against the adversarial agent.

These are the code for the AI-LAB course during Semester 4

Project for the Computational Intelligence course 23/24 - Politecnico di Torino

Implementing search techniques to solve the problem of adversrial game gobang, using the hearistics to improve the efficiency of adversrial search.

Tic Tac Toe Game with AI

The game Mastermind implemented in Rust, with optimal algorithms to play the game.

An AI GO game with AlphaBetaPuring

Play Ataxx against different algorithms

My Tic-Tac-Toe game introduces a challenging twist with an AI opponent employing the MiniMax algorithm. Experience a classic game reimagined, where each move requires strategic thinking to outsmart an AI that anticipates and counters your plays.