Reinforcement Learning via an Optimization Lens

Reinforcement Learning via an Optimization Lens

Simons Institute via YouTube Direct link

Bellman Operator

8 of 21

8 of 21

Bellman Operator

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Classroom Contents

Reinforcement Learning via an Optimization Lens

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

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