Nearly Minimax Optimal Reward-Free Reinforcement Learning

Channel:
United States Simons Institute for the Theory of Computing
Subscribers:
68,800
Published on ● Video Link: https://www.youtube.com/watch?v=WxGpY9O_P14


Duration: 30:50
595 views
12

Simon Du (University of Washington)
https://simons.berkeley.edu/talks/tbd-250
Reinforcement Learning from Batch Data and Simulation



Other Videos By Simons Institute for the Theory of Computing


2020-12-08Central Bank Digital Currency: When Price and Bank Stability Collide
2020-12-08Blockchain as Regulatory Technology: from Code is law to Law as Code
2020-12-07Subquadratic SNARGs in the Random Oracle Model
2020-12-05Panel Discussion
2020-12-05Offline Reinforcement Learning and Model-Based Optimization
2020-12-04Convergence and Sample Complexity of Gradient Methods for the Model-Free Linear Quadratic Regulator
2020-12-04Policy Evaluation under Interference
2020-12-04Stable Reinforcement Learning with Unbounded State Space
2020-12-04Multiagent Reinforcement Learning: Rollout and Policy Iteration
2020-12-04Sample Efficient Reinforcement Learning via Low-Rank Matrix Estimation
2020-12-04Nearly Minimax Optimal Reward-Free Reinforcement Learning
2020-12-03Statistical Efficiency in Offline Reinforcement Learning
2020-12-03Batch Policy Learning in Average Reward Markov Decision Processes
2020-12-03Panel Discussion
2020-12-02The Mean-Squared Error of Double Q-Learning
2020-12-02Q-learning with Uniformly Bounded Variance
2020-12-02Zap Stochastic Approximation and Implications to Q-Learning
2020-12-02Computational/Statistical Gaps for Learning Neural Networks
2020-12-02Uniform Offline Policy Evaluation (OPE) and Offline Learning in Tabular RL
2020-12-02Batch Value-function Approximation with Only Realizability
2020-12-01Reinforcement Learning using Generative Models for Continuous State and Action Space Systems


Tags:
Simons Institute
theoretical computer science
UC Berkeley
Computer Science
Theory of Computation
Theory of Computing
Simon Du
Reinforcement Learning from Batch Data and Simulation