Learning to Act from Observations

Channel:
United States Simons Institute for the Theory of Computing
Subscribers:
68,700
Published on ● Video Link: https://www.youtube.com/watch?v=nM6goCoSz5c


Duration: 54:56
717 views
16

Ashley Edwards (Georgia Tech)
https://simons.berkeley.edu/talks/tbd-200
Theory of Reinforcement Learning Boot Camp



Other Videos By Simons Institute for the Theory of Computing


2020-09-04Stochastic Programming Approach to Optimization Under Uncertainty (Part 1)
2020-09-04A Few Challenge Problems from Robotics
2020-09-04Simulation Methodology: An Overview (Part 1)
2020-09-04Planning and Markov Decision Processes Part 1 (reupload)
2020-09-04Stochastic Programming Approach to Optimization Under Uncertainty (Part 2)
2020-09-04Gradient-Free Optimization With Applications to Power Systems
2020-09-03Recent Results on RL With Gradient Free Optimization
2020-09-03Basics of Algorithm Design and Analysis
2020-09-03Every Optimization Problem Is a Quadratic Program:...
2020-09-03Control Fundamentals
2020-09-02Learning to Act from Observations
2020-09-02Statistical Considerations in Reinforcement Learning (Part 2b)...
2020-09-02Statistical Considerations in Reinforcement Learning (Part 2a)...
2020-09-02Statistical Considerations in Reinforcement Learning (Part 1b):..
2020-09-02Statistical Considerations in Reinforcement Learning (Part 1a):..
2020-09-01The AI Economist: Improving Equality and Productivity with AI-Driven Tax Policies
2020-09-01Batch (Offline) RL (Part 2)
2020-09-01Batch (Offline) RL (Part 1)
2020-09-01Online Learning in MDPs (Part 2)
2020-09-01Online Learning in MDPs (Part 1)
2020-08-31Optimizing Intended Reward Functions: Extracting All the Right Information From All the Right Places


Tags:
Simons Institute
Theory of Computing
Theory of Computation
Theoretical Computer Science
Computer Science
UC Berkeley
Theory of Reinforcement Learning Boot Camp
Ashley Edwards