CS224R - Deep Reinforcement Learning
CS224R - Deep Reinforcement Learning (Spring 2025, Stanford Univ.). Instructor: Prof. Chelsea Finn. Decision-making is central to modern AI systems - from robots and autonomous vehicles to chip design and large language models. Capable AI systems must act and make decisions, not just predict. Deep reinforcement learning (RL) enables this by learning from consequences and feedback, using deep networks to handle high-dimensional observations and complex dynamics.
In this course, you will study practical algorithms for deep RL and how neural networks represent policies, value functions, and world models. You will build methods that learn directly from experience and gain hands-on experience with training, fine-tuning, and evaluating agents on real tasks.
(from Stanford Online)
| Lecture 06 - Q-Learning |
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