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Primal-dual Problems are Hard to Solve
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Classroom Contents
Reinforcement Learning via an Optimization Lens
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- 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
