Machine Learning
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Neural Networks Blog

Reinforcement Learning Playground App

The 'Reinforcement Learning Playground App' is an educational and interactive tool designed to help users understand the fundamentals of reinforcement learning, specifically through the Q-learning algorithm. This app provides a visual and dynamic environment where users can simulate an agent navigating a grid, and see how reward signals influence the agent's learning process.

Features
○ Simulate an Agent Navigating a Grid.
○ As the agent interacts with the environment, the app displays real-time updates (bonus/penalty points).
○ The app visually highlights reward signals, showing how positive rewards (e.g., reaching the goal) and negative rewards (e.g., hitting a wall) influence the agent's learning process.
○ The agent uses the Q-learning algorithm to learn the optimal path to the goal.
○ The visualization helps users understand the reinforcement learning process and the impact of reward signals on the agent's behavior.

Click on the picture to go to the app.

app


The 'Reinforcement Learning Playground App' is a powerful tool for anyone interested in understanding reinforcement learning and the Q-learning algorithm. By providing a visual and interactive environment, the app makes learning about these concepts both engaging and effective.


Get the Reinforcement Learning Playground App complete code.

If you found this project interesting, you can share a coffee with me, by accessing the below link.

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