Reinforcement Learning using Generative Models for Continuous State and Action Space Systems

Published on ● Video Link: https://www.youtube.com/watch?v=TlPaxVVa_WM



Duration: 41:46
1,400 views
27


Rahul Jain (USC)
https://simons.berkeley.edu/talks/tbd-241
Reinforcement Learning from Batch Data and Simulation




Other Videos By Simons Institute for the Theory of Computing


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
2020-12-01Monte Carlo Sampling Approach to Solving Stochastic Multistage Programs
2020-12-01Robust Learning of Stochastic Dynamical Systems
2020-12-01Confident Off-policy Evaluation and Selection through Self-Normalized Importance Weighting
2020-12-01An Equivalence between Loss Functions and Non-Uniform Sampling in Experience Replay
2020-11-30Beyond Worst-Case: Instance-Dependent Optimality in Reinforcement Learning
2020-11-30Learning Multi-Agent Collaborations With Decomposition
2020-11-30Online Learning with A Lot of Batch Data
2020-11-24Ahmed El Alaoui | Fellows Lightning Talks | 6th Annual Industry Day
2020-11-24Computational Complexity of Statistical Inference | Program Presentations | 6th Annual Industry Day
2020-11-24Computational Innovation and Data-Driven Biology | Program Presentations | 6th Annual Industry Day



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