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Network Graph Data Modeling — Solving Tic Tac Toe Without the Minimax Algorithm
Artificial Intelligence   Computer Science   Latest   Machine Learning

Network Graph Data Modeling — Solving Tic Tac Toe Without the Minimax Algorithm

Author(s): Ashutosh Malgaonkar

Originally published on Towards AI.

Here is how tic tac toe looks.

In order for us to start using any kind of data logic on this, we need to identify the board location first. So, let us figure out a system to determine board location.

We will call the columns a,b, and c, and the rows will be numbered 1,2,3

Let us build this out in a quick dataframe, so we can understand what I mean.

Open a notebook at: Welcome To Colaboratory — Colaboratory (

Insert this code into a cell to build out the locations:

import pandas as pddf = pd.DataFrame({'a': [1,2,3], 'b': [1,2,3], 'c':[1,2,3]})df.head()

This is how the dataframe will look. As you can see, it is a matrix. The first row will be a1, b1 and c1, and the second a2,b2,c2 and third will be a3,b3,c3.

This refers to the locations on the tic tac toe board exactly, except now we can refer to this and code the moves.

Convert these to a string:

df['a'] = 'a' + df['a'].astype(str)df['b'] = 'b' + df['b'].astype(str)df['c'] = 'c' + df['c'].astype(str)

Now that I have locations, we can go ahead and use networkx. First, we will install it.

!pip install networkx

Now let us ask the question: why are we installing Networkx? What is the purpose of this… Read the full blog for free on Medium.

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Published via Towards AI

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