MarioPPO implementation uses the TensorFlow machine learning platform
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Updated
Mar 27, 2023 - Python
MarioPPO implementation uses the TensorFlow machine learning platform
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 project aims to implement a reinfrcement learning agent using Proximal Policy Optimization (PPO). And given the Unity environment of the "Karting Microgame", it can be used to train a robust agent on multiple tracks which can compete against other implementations.
In this project I pass through the principles and concepts of Reinforced Learning and I trained an agent to manage the energy resources
Advanced statstical learning course project on reinforcement learning
Unity project. Main goal is to teach the agent to get a key than find the right chest that contains the treasure.
Reinforcement learning project for training an agent to play Atari Breakout, using algorithms like Multiple Tile Coding, Radial Basis Functions, and REINFORCE. Code, insights, and performance analysis provided.
Robot Manipulator Path Planning using Q-Learning – 2D Grid World Case Study
Try out various methods of Reinforcement Learning to automate SnakeGame
Training DQN agents on Classical Discrete Action Open AI gym environments
Snake game reinforcement learning
[ ❌ Deprecated] A reinforcement learning environment, in which the agent learns to navigate and drive a car (ackermann steering) to a goal position.
Classic RL control algorithm implementations found in Sutton and Barto book.
Implementation and comparison of offline RL algorithms
Deep Deterministic Policy Gradient implementation for Reinforcement Learning course taught at Aalto University.
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