This repository hosts the implementation of autonomous vehicle navigation using RL techniques, with a specific emphasis on Deep Q-Networks (DQN) and Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithms. We focus on training a TurtleBot3 robot to navigate autonomously through environments while intelligently avoiding moving obstacles.

Attempt to reimplement the VTC2023-Spring 'Deep Reinforcement Learning-Based Resource Allocation for Cellular V2X Communications' paper

Implementation wumpus with Deep-Q Networks

This project aims to experiment with a car game, exploring whether a DQN (Deep Q Network) agent can autonomously learn to play the game.

RL4CAD: Personalized Decision Making for Coronary Artery Disease Treatment using Offline Reinforcement Learning

This project is a practical exercise to implement and test a reinforcement learning agent using the CartPole environment from OpenAI Gym. The goal is to develop an agent capable of maintaining a pole balanced on a moving cart by applying deep reinforcement learning techniques.