Reinforcement Learning Fundamentals

This lecture covers the basics of reinforcement learning, exploring concepts such as states, actions, rewards, policies, and value functions. The instructor discusses the challenges of learning optimal policies in dynamic environments and the use of neural networks to handle infinite state spaces. The lecture also touches on the connections between reinforcement learning and machine learning, highlighting applications in robotics and game playing.