An interactive Connect Four game with a powerful AI opponent. The AI uses a depth-limited minimax algorithm with alpha-beta pruning. It was written in C++ and compiled to WebAssembly resulting in a blazingly fast AI that can run locally on your browser.

This is a Python script that implements an AI player for the game Connect Four using the Minimax algorithm with alpha-beta pruning. The AI player makes optimal moves by searching through the game tree up to a certain depth and choosing the move that maximizes its chances of winning.

Exploring AI approaches for Connect Four, comparing naive self-play methods with advanced techniques. Features a policy model trained through self-play and minimax, a web interface for interactive gameplay, and aims to quantify efficiency gaps between simple and …

Experience a challenging opponent and witness A*'s effectiveness in anticipating opponent moves, shaping a competitive and engaging Connect Four experience. - ZacRem/AI_Connect4 employs the A* algorithm to power an intelligent Connect Four game.

In this report, we focus on studying two classical reinforcement learning algorithms: Q-learning and Monte-Carlo policy iteration. These techniques are applied to a two-player game called Connect Four, which is a game similar to tic-tac-toe, in order to learn a policy which will allow an AI agent to play the game at a high level.

This Connect Four game was developed using Unreal Engine. The project was created as part of an AI-focused course during my academic studies. The gameplay logic is powered by the Minimax algorithm, enhanced with alpha-beta pruning to optimize decision-making.

2024年12月21日 · Comparing AI approaches through simulations; Enhancing the AI with machine learning; Optimization and debugging tips; By the end, you‘ll have mastered the skills to code an unbeatable AI for Connect Four or even apply them to other turn-based games. The Theory Behind Connect Four AI

For our ECE 5760: Advanced Microcontrollers final project, we decided to create a Connect Four AI in hardware on the FPGA. The goal was not only to develop an AI with a certain degree of challenge for a human player, but also to accelerate the program to perform and make decisions much faster than a software-based AI with the same behavior ...

This AI simulates all possible moves for a certain depth of turns and assigns each potential board a score. Using the minimax algorithm, it then chooses the best move. I have found that a depth of 4 plays quickly, while beating human players pretty consistently.

2024年4月22日 · In this article, we‘ll walk through how to create an expert-level Connect Four AI using Python. The AI will use the minimax algorithm with alpha-beta pruning to select the optimal move by looking several steps ahead. By the end, you‘ll understand the key concepts needed to create AIs for Connect Four and other similar games.