Completed
Puddle World with Neural Networks
Class Central Classrooms beta
YouTube videos curated by Class Central.
Classroom Contents
Reinforcement Learning via an Optimization Lens
Automatically move to the next video in the Classroom when playback concludes
- 1 Intro
- 2 Reinforcement karning: Learning to make decisions
- 3 Online vs. Offline (Batch) RL: A Basic View
- 4 Outline
- 5 Markov Decision Process (MDP)
- 6 MDP Example: Deterministic Shortest Path
- 7 More General Case: Bellman Equation
- 8 Bellman Operator
- 9 When Bellman Meets Gauss: Approximate DP
- 10 Divergence Example of Tsitsiklis & Van Roy (96)
- 11 Does It Matter in Practice?
- 12 A Long-standing Open Problem
- 13 Linear Programming Reformulation
- 14 Why Solving for Fixed Point Directly is Hard?
- 15 Addressing Difficulty #2: Legendre-Fenchel Transformation
- 16 Reformulation of Bellman Equation
- 17 Primal-dual Problems are Hard to Solve
- 18 A New Loss for Solving Bellman Equation
- 19 Eigenfunction Interpretation
- 20 Puddle World with Neural Networks
- 21 Conclusions