🤖 Training an RL agent to balance a cartpole in the OpenAI Gym environment.
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Updated
Oct 3, 2023 - Python
🤖 Training an RL agent to balance a cartpole in the OpenAI Gym environment.
Reinforcement Learning with Stable Baselines3: Train and evaluate a CartPole agent using Stable Baselines3 library. Includes code for training, saving, and testing the model, along with a GIF visualization of the trained agent.
This is an intelligent cartpole which knows how to balance itself.
Implementing some RL algorithms (using PyTorch) on the CartPole environment by OpenAI.
Using DRL algorithms like Policy gradients, A2C on game environments like CartPole-v0 and other Atari games
Solving the gym cartpole v0 problem
CartPole environment using Stable BaseLines library
Solving CartPole using Distributional RL
CartPole-v0 solved using the REINFORCE algorithm
Solved CartPole-v0 with REINFORCE algorithm.
My attempt to solve the classic CartPole-v0 problem using (Deep) Reinforcement Learning
simple and minimal implementation of DQN using target network.
A few machine learning projects that I made using PyTorch
Hill Climbing Algorithm implemented for the Cart Pole Environment.
Experiments on Reinforcement Learning with OpenAI Gyms
OpenAI CartPole-v0 DeepRL-based solutions (DQN, DuelingDQN, D3QN)
PGuNN - Playing Games using Neural Networks
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