CartPole-v1 Reinforcement Learning 🏋️‍♂️🤖

I tried Reinforcement Learning for the first time!
I was always amazed by how giant robots can be trained through simulations using reinforcement learning.
I am grateful to try this for the first time in my life with the CartPole-v1 environment from OpenAI Gym.

In this project, I trained an agent to balance a pole on a moving cart by applying a fixed amount of force either to the left or right side.

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🚀 Tech Stack

• OpenAI Gym environment: CartPole-v1
• Pygame for visualization

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🎯 Goal

The agent learns to keep the pole balanced for as long as possible without falling.

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📌 Future Work

• Improve training with better algorithms (e.g., DQN, Policy Gradients)
• Save and load trained models
• Compare results with different hyperparameters

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🙌 Acknowledgements

Thanks to OpenAI Gym for providing such an amazing environment to learn reinforcement learning.