The implementation of some reinforcement learning techniques like (Q-learning, SARSA, DQN) in two assignments and one big project.
-
Updated
Nov 12, 2022 - Jupyter Notebook
The implementation of some reinforcement learning techniques like (Q-learning, SARSA, DQN) in two assignments and one big project.
Repository for the final project of the "Computational Intelligence" course @ PoliTo, 2022/2023
Decision Making Under Uncertainty (DMU) final project.
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 utilize reinforcement learning (RL) techniques to train an artificial intelligence agent capable of playing the iconic Super Mario game.
Unity project. Main goal is to teach the agent to get a key than find the right chest that contains the treasure.
Self Training Sneak Game with Reinforcement Learning
In this project I pass through the principles and concepts of Reinforced Learning and I trained an agent to manage the energy resources
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.
This code repository contains the implementation of Q-Learning agent for Mountain Car game. It is part of the lab exercise for the COSC-604 Artificial Intelligence course for masters students at Khalifa University.
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.
Advanced statstical learning course project on reinforcement learning
Using a Deep Q Network(DQN) to play Atari Breakout
Snake game reinforcement learning
A simple implementation of the Proximal Policy Optimization (PPO) algorithm using Pytorch.
Add a description, image, and links to the reinforcement-learning topic page so that developers can more easily learn about it.
To associate your repository with the reinforcement-learning topic, visit your repo's landing page and select "manage topics."