Exploring popular reinforcement learning environments in a beginner-friendly way, focusing on the Q-learning method to solve the 'Frozen Lake' environment.
An article discussing the use of Deep Q-Networks (DQNs) in reinforcement learning, which combines the principles of Q-Learning with function approximation capabilities of neural networks to address limitations of traditional Q-learning such as scalability issues and inability to handle continuous state and action spaces.
