Knowledge-based backtracking algorithm to win the game of connect 4. This work is based on the master thesis "A Knowledge-based Approach of Connect-Four" from Victor Allis back in 1988.
-
Updated
Dec 2, 2022 - Python
Knowledge-based backtracking algorithm to win the game of connect 4. This work is based on the master thesis "A Knowledge-based Approach of Connect-Four" from Victor Allis back in 1988.
An asynchronous implementation of AlphaZero, a self-play reinforcement learning algorithm.
Deep Reinforcement Learning algorithms to play Connect4 using a combination of Supervised Learning and Reinforcement Learning
🤖 Pretty perfect bot remembering only perfect moves for overcoming the perfect AI written by a perfect guy
Play Connect4 against an intelligent AI agent using Minimax Algorithm with and without Pruning
A strategic Connect4 game powered by multiple AI opponents, built with Python. Features various algorithms – from Minimax to AI-Agents – offering challenging gameplay for beginners and experts alike.
connect4 game and ai player with text based user interface
Intelligent Agent to play Connect-4 with a modifiable depth aided with a decision tree visualizer to trace the agent's decision making process
Little program for MCTS and alpha-beta-pruning that can play connect4 against each other.
Connect 4 is a classic two-player strategy game where players take turns dropping colored discs into a grid, aiming to align four of their discs in a row—horizontally, vertically, or diagonally—before their opponent. In the AI-enhanced version, one player competes against a computer opponent programmed to make intelligent, strategic moves.
A GUI based connect 4 game that uses voice as input
Predicting Win/Loss/Draw on the Connect Four dataset with Tsetlin Machines
Project using minmax and alpha beta pruning to make ai for tictactoe and connect4 with gui using pygame
Implemented the Minimax algorithm with Alpha-Beta pruning for an AI player in Connect4
Artificial intelligence solving Tic Tac Toe and Connect 4 games using minimax algorithm optimised by alpha-beta prunning
Implementation of connect 4 game in python using alpha beta pruning
The goal of this project is to implement a Connect 4 game using the Minimax algorithm with alpha-beta pruning. We design an appropriate Connect 4 board evaluation function to be used as the algorithm’s utility function. Our game should allow a human player to play against our algorithm. The algorithm should use a depth-first strategy when explor…
This is a simple Connect Four game implemented in Python with ability to play against computer
Connect 4 game against AI in Python
Add a description, image, and links to the connect4-ai-game topic page so that developers can more easily learn about it.
To associate your repository with the connect4-ai-game topic, visit your repo's landing page and select "manage topics."