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Properly display π*

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Artagon
2022-12-16 20:31:49 +01:00
parent 713f12295d
commit 0744d542ad
1 changed files with 3 additions and 3 deletions
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units/en/unit2/two-types-value-based-methods.mdx
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@@ -10,7 +10,7 @@ The value of a state is the **expected discounted return** the agent can get i
But what does it mean to act according to our policy? After all, we don't have a policy in value-based methods since we train a value function and not a policy.
</Tip>
Remember that the goal of an **RL agent is to have an optimal policy π.**
Remember that the goal of an **RL agent is to have an optimal policy π\*.**
To find the optimal policy, we learned about two different methods:
@@ -35,8 +35,8 @@ Consequently, whatever method you use to solve your problem, **you will have a
So the difference is:
- In policy-based, **the optimal policy (denoted π*) is found by training the policy directly.**
- In value-based, **finding an optimal value function (denoted Q* or V*, we'll study the difference after) in our leads to having an optimal policy.**
- In policy-based, **the optimal policy (denoted π\*) is found by training the policy directly.**
- In value-based, **finding an optimal value function (denoted Q\* or V\*, we'll study the difference after) in our leads to having an optimal policy.**
<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit3/link-value-policy.jpg" alt="Link between value and policy"/>