La nostra soluzione per la Tablut Challenge 2022 ♟️ (Fondamenti di Intelligenza Artificiale M)
This is a fully fledged 2 or 1 player tic-tac-toe game written in TypeScript using Ionic Framework.
An implementation of Minimax, Alpha-Beta and Monte-Carlo Tree Search to play Connect 4
Kotlin AI for the Softwarechallenge 2018 featuring the game "Hase und Igel"
A lightweight implementation of Dr. Fill
Portfolio of AI projects developed during my Udacity AI Nanodegree, covering Planning AI, Constraint Satisfaction, Hidden Markov Models, and Search algorithms.
♟️ Athena is a Python-based chess engine using negamax algorithm with alpha-beta pruning, piece-square tables, Simplified Evaluation Function and move ordering♟️
A simple and intuitive Chess AI in Python.
GETVar 🧬👨🏻💻 [DO NOT USE THIS VERSION
AI-lab assignments
Hybrid Reinforcement Learning and minimax agent for Tablut game. Combines PPO trained value networks with alpha beta search for competitive play.
🔍 Monitor network activity in real-time with LazyNet, a terminal-based tool that provides clear insights and management for processes and connections.
An AI game agent that uses minimax and alpha-beta pruning to serach what the next best move of the game is.
Add a description, image, and links to the alpha-beta-pruning topic page so that developers can more easily learn about it.
To associate your repository with the alpha-beta-pruning topic, visit your repo's landing page and select "manage topics."