Lesson plan

Policy gradient method

Policy gradient methods are a class of reinforcement learning algorithms and a sub-class of policy optimization methods. Unlike value-based methods which learn a value function to derive a policy, policy optimization methods directly learn a policy function \pi that selects actions without consulting a value function. For policy gradient to apply, the policy function \pi_\theta is parameterized by a differentiable parameter \theta .

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Article summary

Policy gradient methods are a class of reinforcement learning algorithms and a sub-class of policy optimization methods. Unlike value-based methods which learn a value function to derive a policy, policy optimization methods directly learn a policy function \pi that selects actions without consulting a value function. For policy gradient to apply, the policy function \pi_\theta is parameterized by a differentiable parameter \theta .

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Discussion questions

  1. Summarise the article in your own words. Which single claim would you verify first, and why?
  2. Which claim in this article is most likely to be revised as the sources update? How would you check its current status?
  3. If two sources disagreed about one of these facts, what would you need in order to trust one over the other?

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Key claims and bibliography are generated from the same tracked claims and sources as the article page.