Stanford AA228/CS238 Decision Making Under Uncertainty I Policy Gradient Estimation and Optimization

October 26, 2023
Joshua Ott of Stanford University
Learn more about the speaker: profiles.stanf...
This course introduces decision making under uncertainty from a computational perspective and provides an overview of the necessary tools for building autonomous and decision-support systems. Following an introduction to probabilistic models and decision theory, the course will cover computational methods for solving decision problems with stochastic dynamics, model uncertainty, and imperfect state information. Topics include Bayesian networks, influence diagrams, dynamic programming, reinforcement learning, and partially observable Markov decision processes. Applications cover air traffic control, aviation surveillance systems, autonomous vehicles, and robotic planetary exploration.
View the course website: aa228.stanford...
Enroll in the course: online.stanfor...

[@himatejanallani]

Thank you Stanford Online for uploading this lecture for public viewing. I am quite intrigued by this lecture and would love to see the rest of the course. As someone who follows Stanford lectures through RUclips, I sincerely request you make the lecture series available for public. As always, you guys are doing a great job in democratising the knowledge.

[@sarahsalt-l8n]

I appreciate you making this lecture available to the community, and I am very much looking forward to more lectures in the future! Certain probabilistic frameworks that you elucidate in this lecture finally feel clearer to me.

[@faridmusayev2587]

Thank you for uploading this lecture. It would be great to have full lectures uploaded (if available). The accompanying course book is really great (with both code and exercises) and would be nice to supplement it with video lectures.

[@vedantgosavi20]

This is truly good ! Need more lectures on this, please ​@stanfordonline !

[@stanfordonline]

Thanks for your feedback, we will share with our team!

[@takihasan8310]

Is it possible to get more lectures of the course, I am stoked for that.

[@theneumann7]

Thanks for sharing all this content

[@pj-nz6nm]

Is there are more lectures.

[@stanfordonline]

Thanks for your comment! We do not have other lectures from this course available at this time, but we will share your interest with our team :)

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