play · tinker · learn
Welcome to TicTacToe Menace: The Learning Enemy! In this app, you play against a computer opponent based on the Menace Matchbox Calculator - an example of Reinforcement Learning.
The special feature: The learning table can be stored both locally and in a MySQL database, so that the opponent can learn from several players at the same time!
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K-Means Clustering is a popular algorithm in the field of unsupervised learning, which is used to divide data into groups or clusters. This approach makes it possible to identify patterns in data without requiring prior labels. For an introduction to the topic and a fun board game to illustrate the concepts of unsupervised learning, you can find information on this page. There you will find materials that help you better understand the basics of K-Means Clustering and apply them in practice.
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In this article we outline the development of the QField with Scratch. We start by drawing the playing field and implementing the random movement of Scratch. In the next step, we introduce the Q table, which serves as the basis for reinforcing learning. Finally, we visualize Scratch's decisions through drawn arrows that represent his path on the playing field.
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The QField serves to recreate the process of reinforcement learning with a piece of paper and a pen. This is about learning a way by using the unplugged algorithm. Unlike other algorithms that aim for optimal solutions, this approach focuses on learning through trial and feedback.
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The NIM game is a game in which two players play against each other. It is excellent to clarify machine learning according to the principle of reinforcement learning.
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