Tic-tac-toe with minmax algorithm.

Related tags

AlgorithmsTic-tac-toe
Overview

Tic-tac-toe

Tic-tac-toe game with minmax algorithm which is a research algorithm his objective is to find the best move to play by going through all the different scenarios.

General info

The first message shows the player different options, the first one : if he wants to play against another player, the second one : if he wants to play against the robot, if it's the case, he must choose a symbol (X or O).

After that the player must tap a number between 1 and 9 to choose where to put an X or O.

Different messages are displayed at the end of the game ,there is one that shows who won (one of the players or the robot),and another showing that nobody won.

Project files

main.py

Launch a Tic-tac-toe game between two player or player and robot, display the sequence of the game and the winner at the end.

minmax.py

Contains the functions:

  • minimax(board,isMax) :In Minimax the two players are called maximizer and minimizer. The maximizer tries to get the highest score possible while the minimizer tries to do the opposite and get the lowest score possible ,every board state has a value associated with it. In a given state if the maximizer has upper hand then, the score of the board will tend to be some positive value. If the minimizer has the upper hand in that board state then it will tend to be some negative value. The values of the board are calculated by some heuristics which are unique for every type of game.
  • findBestMoveForO(board) : To check whether or not the current move is better than the best move we take the help of minimax() function which will consider all the possible ways the game can go and returns the best value for that move, assuming the opponent also plays optimally
  • findBestMoveForX(board) : the same operation of the function findBestMoveForO(board) the only difference it treats the case where the X will play

tictactoe.py

Contains the functions:

  • showTable(table):show tictactoe board
  • winCheck(board):show tictactoe board
  • endCheck(table):check if the game is end

Technologies

Project is created with:

  • Python version : 3.10

Setup

To run this project:

$ python main.py 
or 
$ py main.py
Repository for data structure and algorithms in Python for coding interviews

Python Data Structures and Algorithms This repository contains questions requiring implementation of data structures and algorithms concepts. It is us

Prabhu Pant 1.9k Jan 01, 2023
This project consists of a collaborative filtering algorithm to predict movie reviews ratings from a dataset of Netflix ratings.

Collaborative Filtering - Netflix movie reviews Description This project consists of a collaborative filtering algorithm to predict movie reviews rati

Shashank Kumar 1 Dec 21, 2021
A calculator to test numbers against the collatz conjecture

The Collatz Calculator This is an algorithm custom built by Kyle Dickey, used to test numbers against the simple rules of the Collatz Conjecture. Get

Kyle Dickey 2 Jun 14, 2022
Data Model built using Logistic Regression Algorithm on Python.

Logistic-Regression Problem Statement: Your client is a retail banking institution. Term deposits are a major source of income for a bank. A term depo

Hemanth Babu Muthineni 0 Dec 25, 2021
N Queen Problem using Genetic Algorithm

The N Queen is the problem of placing N chess queens on an N×N chessboard so that no two queens attack each other.

Mahdi Hassanzadeh 2 Nov 11, 2022
This is an implementation of the QuickHull algorithm in Python. I

QuickHull This is an implementation of the QuickHull algorithm in Python. It randomly generates a set of points and finds the convex hull of this set

Anant Joshi 4 Dec 04, 2022
Distributed Grid Descent: an algorithm for hyperparameter tuning guided by Bayesian inference, designed to run on multiple processes and potentially many machines with no central point of control

Distributed Grid Descent: an algorithm for hyperparameter tuning guided by Bayesian inference, designed to run on multiple processes and potentially many machines with no central point of control.

Martin 1 Jan 01, 2022
A lightweight, pure-Python mobile robot simulator designed for experiments in Artificial Intelligence (AI) and Machine Learning, especially for Jupyter Notebooks

aitk.robots A lightweight Python robot simulator for JupyterLab, Notebooks, and other Python environments. Goals A lightweight mobile robotics simulat

3 Oct 22, 2021
A priority of preferences for teacher assignment problem

Genetic-Algorithm-for-Assignment-Problem A priority of preferences for teacher assignment problem Keywords k-partition; clustering; education 4.0 Abst

hades 2 Oct 31, 2022
FPE - Format Preserving Encryption with FF3 in Python

ff3 - Format Preserving Encryption in Python An implementation of the NIST approved FF3 and FF3-1 Format Preserving Encryption (FPE) algorithms in Pyt

Privacy Logistics 42 Dec 16, 2022
Parameterising Simulated Annealing for the Travelling Salesman Problem

Parameterising Simulated Annealing for the Travelling Salesman Problem Abstract The Travelling Salesman Problem is a well known NP-Hard problem. Given

Gary Sun 55 Jun 15, 2022
Planning Algorithms in AI and Robotics. MSc course at Skoltech Data Science program

Planning Algorithms in AI and Robotics course T2 2021-22 The Planning Algorithms in AI and Robotics course at Skoltech, MS in Data Science, during T2,

Mobile Robotics Lab. at Skoltech 6 Sep 21, 2022
It is a platform that implements some path planning algorithms.

PathPlanningAlgorithms It is a platform that implements some path planning algorithms. Main dependence: python3.7, opencv4.1.1.26 (for image show) Tip

5 Feb 24, 2022
There are some basic arithmatic in Pattern Recognization and Machine Learning writed in Python in this repository

There are some basic arithmatic in Pattern Recognization and Machine Learning writed in Python in this repository

1 Nov 19, 2021
Supplementary Data for Evolving Reinforcement Learning Algorithms

evolvingrl Supplementary Data for Evolving Reinforcement Learning Algorithms This dataset contains 1000 loss graphs from two experiments: 500 unique g

John Co-Reyes 42 Sep 21, 2022
A Python program to easily solve the n-queens problem using min-conflicts algorithm

QueensProblem A program to easily solve the n-queens problem using min-conflicts algorithm Performances estimated with a sample of 1000 different rand

0 Oct 21, 2022
Slight modification to one of the Facebook Salina examples, to test the A2C algorithm on financial series.

Facebook Salina - Gym_AnyTrading Slight modification of Facebook Salina Reinforcement Learning - A2C GPU example for financial series. The gym FOREX d

Francesco Bardozzo 5 Mar 14, 2022
8 Puzzle with A* , Greedy & BFS Search in Python

8_Puzzle 8 Puzzle with A* , Greedy & BFS Search in Python Python Install Python from here. Pip Install pip from here. How to run? 🚀 Install 8_Puzzle

I3L4CK H4CK3l2 1 Jan 30, 2022
Implementation of an ordered dithering algorithm used in computer graphics

Ordered Dithering Project In this project, we use an ordered dithering method to turn an RGB image, first to a gray scale image and then, turn the gra

1 Oct 26, 2021
Leveraging Unique CPS Properties to Design Better Privacy-Enhancing Algorithms

Differential_Privacy_CPS Python implementation of the research paper Leveraging Unique CPS Properties to Design Better Privacy-Enhancing Algorithms Re

Shubhesh Anand 2 Dec 14, 2022