Computer Science is the study of how computers work and how we can use them to solve problems. By studying computer science, we can use technology to make our lives easier and more efficient.

The goal of my project was to find if a neural network would be able to learn how to play Connect 4 (a board game where the goal is to get four tokens in a row) well enough that it could beat a human opponent. A neural network is an artificial intelligence program that uses a network of connections between input values and output values to eventually learn how to do something. 

Can a neural network (a program that learns through practice) teach itself to play Connect 4 well enough to beat a person? You build the network and train it using a genetic algorithm. This method creates many versions of the program and keeps the ones that perform best.

The network plays against a simulated opponent over many rounds. It learns to beat that opponent reliably. But when a human player with a different strategy steps in, the human still wins.

The network learned to beat one style of play rather than the game itself. Training it against several opponents with different strategies could help it play more broadly.

Title: Artificial Intelligence: Can a Neural Network Learn to Play Connect 4?

Objectives/Goals

The goal of my project was to find if a neural network would be able to learn
how to play Connect 4 (a
board game where the goal is to get four tokens in a row) well enough that it
could beat a human
opponent. A neural network is an artificial intelligence program that uses a
network of connections
between input values and output values to eventually learn how to do something.
A neural network uses
weights to determine the output for the given input. To find a good set of
weights, the neural network can
be trained. One type of training method for a neural network is a genetic
algorithm. The genetic algorithm
creates a model of individuals, based on the set of weights. It uses the basic
idea of natural selection to
eliminate the weak and promote the strong.

Methods/Materials

I created a computer program that played Connect 4 with a simulated opponent for
the neural network to
play. Then I tried out different ways of training a neural network. Finally, I
created a training method for
the neural network, using a genetic algorithm.
Results
The neural network learned to beat the simulated opponent that I could rarely
beat, but I could still beat
the neural network because I had a different strategy than the opponent.

Conclusions/Discussion

The neural network did not learn to play a wide variety of strategies.
Therefore, it learned to play the
opponent, not the game in general. If I had played the neural network instead of
the opponent, it probably
would have been better at playing me. In conclusion, the neural network did not
have all of the
information it needs to be very good at the game of Connect 4. It might be
improved by having it play
against me or several opponents with different strategies.

Summary Statement

My project involved creating and training an artificial neural network to play
the game of Connect 4.

Help Received

My dad showed me how a genetic algorithm worked and helped with editing.

Neural Networks and Connect 4 Strategy

Can a neural network learn how to play a board game?

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Math is all about numbers, patterns, and solving problems. Computer science is about using math and technology to create computer programs and solve real-world problems. Together, they help us understand how things work, how to solve problems, and how to use technology to make our lives better!

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Neural Networks and Connect 4 Strategy

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