Reinforcement Learning (RL) is a subfield of machine learning that focuses on how agents should take actions in an environment to maximize some notion of cumulative reward. This page lists some projects related to Reinforcement Learning.
Project 1: CartPole Balancing
CartPole is a classic RL problem where the goal is to balance a pole on a cart. This project can be implemented using various RL algorithms such as Q-learning or Policy Gradient methods.
Project 2: Mountain Car
Mountain Car is another RL problem where the goal is to drive a car up a mountain. This project can be implemented using different RL algorithms to find the optimal policy.
Project 3: Atari Breakout
Atari Breakout is a classic video game where the goal is to break blocks using a ball. This project can be implemented using deep reinforcement learning algorithms such as Deep Q-Network (DQN) or Proximal Policy Optimization (PPO).