Deep Reinforcement Learning
CS224R
Humans, animals, and robots faced with the world must make decisions and take actions in the world. Moreover, the decisions they choose affect the world they exist in - and those outcomes must be taken into account. This course is about algorithms for deep reinforcement learning - methods for learning behavior from experience, with a focus on practical algorithms that use deep neural networks to learn behavior from high-dimensional observations.
Topics Include
- Methods for learning from demonstrations
- Both model-based and model-free deep RL methods
- Methods for learning from offline datasets and more advanced techniques for learning multiple tasks such as goal-conditioned RL, meta-RL, and unsupervised skill discovery
What You Need to Succeed
- A conferred bachelor’s degree with an undergraduate GPA of 3.0 or better
What You Need To Get Started
Before enrolling in your first graduate course, you must complete an online application.
Don’t wait! While you can only enroll in courses during open enrollment periods, you can complete your online application at any time.
Once you have enrolled in a course, your application will be sent to the department for approval. You will receive an email notifying you of the department's decision after the enrollment period closes. You can also check your application status in your mystanfordconnection account at any time.
Learn more about the graduate application process.
