Reinforcement learning tutorials
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Updated
Mar 25, 2023 - Python
Reinforcement learning tutorials
Reinforcement Learning Scripts
Q-Learning, Actor-Critics, Proximal-Policy Optimization reinforcement learning algorithms in bipedal walker-v2 environment
Pytorch implementation of the Deep Deterministic Policy Gradients for Continuous Control
In this project I create agent for the BipedalWalker environment using the Proximal Policy Optimization (PPO) algorithm from the stablebaselines3 library. The agent is trained to navigate the BipedalWalker environment, which is a simulated robot with two legs.
PyTorch application of reinforcement learning Advanced Policy Gradient algorithms in OpenAI BipedalWalker- PPO
An ESP32 + Python controlled biped robot powered by servo motors.
[MATLAB] Various Passive Dynamic Walking Robot Simulation Code!
Proximal Policy Optimization method in Pytorch
This is a Biped simulated on pybullet physics engine, walking
Remember the sad Marvin from "Hitchhiker's guide to the galaxy"? In this project we train him to walk from the scratch using only pure python with numpy!
ROS-based BD1 droid from Star Wars The Fallen Order
Own researches in reinforcement learning using openai-gym.
Neural network and Reinforcement learning algorithms for the Bipedal Walker problem
32 projects in the framework of Deep Reinforcement Learning algorithms: Q-learning, DQN, PPO, DDPG, TD3, SAC, A2C and others. Each project is provided with a detailed training log.
Utilizes Q-learning, DQN, and TD3 reinforcement learning algorithms to teach BipedalWalker to walk
Programmatically Interpretable Reinforcement Learning
Usage of genetic algorithms to train a neural network in multiple OpenAI gym environments.
Solving OpenAI Gym problems.
Deep Reinforcement Learning by using Proximal Policy Optimization and Random Network Distillation in Tensorflow 2 and Pytorch with some explanation
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