Paper Title
IMPLEMENTING GAME THEORY ON TIC-TAC-TOE GAME

Abstract
Abstract - Noughts and crosses also known asTic-tac-toe is a two-player game played on a 3x3 grid. In order to obtain three of their symbols (Noughts or Crosses) in a row before the other player does, each player alternately places a "X" or an "O" on the grid. The game is a draw if every square on the grid is filled but no one has won. A type of machine learning called reinforcement learning involves an agent learning by interacting with its environment and receiving rewards or punishments for certain actions. The goal of reinforcement learning is to learn the optimal policy, or the set of actions that will maximize the reward. The primary objective of this research is likely to create a reinforcement learning algorithm that can master the game of Noughts and Crosses and possibly outperform a human player. This could entail adopting a self-play strategy, where the algorithm competes against itself and acquires knowledge from the results of the games or training the algorithm on a large dataset of tic-tac-toe games. Examining various reinforcement learning algorithms or methodologies, evaluating the efficacy of various strategies, and contrasting the algorithm's performance with that of human players may all be further study goals.