26-27 August 2017 | Berkeley CA
Core Lecture 1 Intro to MDPs and Exact Solution Methods -- Pieter Abbeel (video | slides)
Core Lecture 2 Sample-based Approximations and Fitted Learning -- Rocky Duan (video | slides)
Core Lecture 4a Policy Gradients and Actor Critic -- Pieter Abbeel (video | slides)
Core Lecture 4b Pong from Pixels -- Andrej Karpathy (video | slides)
Core Lecture 5 Natural Policy Gradients, TRPO, and PPO -- John Schulman (video | slides)
Core Lecture 6 Nuts and Bolts of Deep RL Experimentation -- John Schulman (video | slides)
Core Lecture 7 SVG, DDPG, and Stochastic Computation Graphs -- John Schulman (video | slides)
Core Lecture 8 Derivative-free Methods -- Peter Chen (video | slides)
Core Lecture 9 Model-based RL -- Chelsea Finn (video | slides)
Core Lecture 10a Utilities -- Pieter Abbeel (video | slides)
Core Lecture 10b Inverse RL -- Chelsea Finn (video | slides)
Frontiers Lecture I: Recent Advances, Frontiers and Future of Deep RL -- Vlad Mnih (video | slides)
Frontiers Lecture II: Recent Advances, Frontiers and Future of Deep RL -- Sergey Levine (video | slides)
Core Lecture 1 Intro to MDPs and Exact Solution Methods (Pieter Abbeel)
Core Lecture 1 Intro to MDPs and Exact Solution Methods (Pieter Abbeel)
Core Lecture 2 Sample-based Approximations and Fitted Learning (Yan (Rocky) Duan)
Core Lecture 2 Sample-based Approximations and Fitted Learning (Yan (Rocky) Duan)
Core Lecture 3 DQN + variants (Vlad Mnih)
Core Lecture 3 DQN + variants (Vlad Mnih)
Core Lecture 4a Policy Gradients and Actor Critic (Pieter Abbeel)
Core Lecture 4a Policy Gradients and Actor Critic (Pieter Abbeel)
Core Lecture 4b Pong from Pixels (Andrej Karpathy)
Core Lecture 4b Pong from Pixels (Andrej Karpathy)
Core Lecture 5 Natural Policy Gradients, TRPO, and PPO (John Schulman)
Core Lecture 5 Natural Policy Gradients, TRPO, and PPO (John Schulman)
Core Lecture 6 Nuts and Bolts of Deep RL Experimentation
Core Lecture 6 Nuts and Bolts of Deep RL Experimentation
Core Lecture 7 SVG, DDP, and Stochastic Computation Graphs
Core Lecture 7 SVG, DDP, and Stochastic Computation Graphs
Core Lecture 8 Derivative Free Methods (Xi (Peter) Chen)
Core Lecture 8 Derivative Free Methods (Xi (Peter) Chen)
Core Lecture 9 Model-based RL (Chelsea Finn)
Core Lecture 9 Model-based RL (Chelsea Finn)
Core Lecture 10a Utilities (Pieter Abbeel)
Core Lecture 10a Utilities (Pieter Abbeel)
Core Lecture 10b Inverse RL (Chelsea Finn)
Core Lecture 10b Inverse RL (Chelsea Finn)
Frontiers Lecture I: Recent Advances, Frontiers and Future of Deep RL (Vlad Mnih)
Frontiers Lecture I: Recent Advances, Frontiers and Future of Deep RL (Vlad Mnih)
Frontiers Lecture II: Recent Advances, Frontiers and Future of Deep RL (Sergey Levine)
Frontiers Lecture II: Recent Advances, Frontiers and Future of Deep RL (Sergey Levine)