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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
  • 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
  • Greedy policy improvement
  • ε-Greedy policy improvement
    • 1-ε 의 확률로 greedy action
    • ε의 확률로 random action
  • GLIE: Greedy in the Limit with Infinite Exploration
    • ε이 step k에서 1/k로 점점 작아진다면(fade out) GLIE이다
  • 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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