jinglescode/reinforcement-learning-tic-tac-toe

A reinforcement learning algorithm for agents to learn the tic-tac-toe, using the value function.

26
/ 100
Experimental

This project helps anyone interested in understanding how an artificial intelligence can learn optimal strategies through trial and error. You'll input a simple game like Tic-Tac-Toe, and it will output a 'trained' AI agent capable of playing intelligently by evaluating the potential future value of each move. It's ideal for students or enthusiasts exploring the fundamentals of reinforcement learning.

No commits in the last 6 months.

Use this if you want to see a clear, practical example of a reinforcement learning agent learning to play a game by understanding the 'value' of different game states.

Not ideal if you're looking for a complex, general-purpose reinforcement learning framework for advanced research or real-world applications beyond simple games.

AI-learning game-strategy intro-AI machine-learning-concepts
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 4 / 25

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Stars

21

Forks

1

Language

JavaScript

License

Apache-2.0

Last pushed

Sep 12, 2020

Commits (30d)

0

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