Markov Decision Processes 2 – Reinforcement Learning | Stanford CS221: AI (Autumn 2019)
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/2Zv1JpK
Topics: Reinforcement learning, Monte Carlo, SARSA, Q-learning, Exploration/exploitation, function approximation
Percy Liang, Associate Professor & Dorsa Sadigh, Assistant Professor - Stanford University
http://onlinehub.stanford.edu/
Associate Professor Percy Liang
Associate Professor of Computer Science and Statistics (courtesy)
https://profiles.stanford.edu/percy-liang
Assistant Professor Dorsa Sadigh
Assistant Professor in the Computer Science Department & Electrical Engineering Department
https://profiles.stanford.edu/dorsa-sadigh
To follow along with the course schedule and syllabus, visit:
https://stanford-cs221.github.io/autumn2019/#schedule
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/2Zv1JpK
Topics: Reinforcement learning, Monte Carlo, SARSA, Q-learning, Exploration/exploitation, function approximation
Percy Liang, Associate Professor & Dorsa Sadigh, Assistant Professor – Stanford University
http://onlinehub.stanford.edu/
Associate Professor Percy Liang
Associate Professor of Computer Science and Statistics (courtesy)
https://profiles.stanford.edu/percy-liang
Assistant Professor Dorsa Sadigh
Assistant Professor in the Computer Science Department & Electrical Engineering Department
https://profiles.stanford.edu/dorsa-sadigh
To follow along with the course schedule and syllabus, visit:
https://stanford-cs221.github.io/autumn2019/#schedule
