머신러닝스터디/2017/Reinforcement Learning/ (rev. 1.11)

머신러닝스터디/2017/Reinforcement Learning/

Reinforcement Learning ¶

Lecture 4: Model Free Prediction ¶

Lecture 5: Model Free Control ¶

동영상 주소: https://www.youtube.com/watch?v=0g4j2k_Ggc4&t=2466s

on policy vs off policy
ε-Greedy
Policy Iteration: Iterate these two step
1. Policy evaluation
  - Evaluate value function with given policy π
2. Policy Improvement
  - Update policy in current state s, current action a, current reward r to next state s', nest action a' -> sarsa
Sarsa
- one step update policy TD?
- on policy
- Sarsa는 다음과 같은 조건에서 converge한다
  1. GLIE sequence of policies
  2. Robinson Monro sequence of step sizes

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