Implementation of connect 4 game in python using alpha beta pruning
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Updated
Dec 16, 2020 - Python
Implementation of connect 4 game in python using alpha beta pruning
A Connect Four game implementation in Python using Pygame, featuring an AI opponent powered by the Minimax algorithm with alpha-beta pruning.
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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.
A.I Connect 4 game written in Python and using the Minimax algorithm with Alpha-Beta pruning and a depth.
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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…
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Little program for MCTS and alpha-beta-pruning that can play connect4 against each other.
Intelligent Agent to play Connect-4 with a modifiable depth aided with a decision tree visualizer to trace the agent's decision making process
Play Connect4 against an intelligent AI agent using Minimax Algorithm with and without Pruning
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