题目
题目

CS7646 Course Content Quiz #10

多项选择题

How does exploration in Q-learning help to improve the learning process? (Select all that apply)  

选项
A.Exploration rapidly decreases the learning rate (α) to avoid overfitting the model.
B.Exploration enhances learning by increasing the speed of convergence by focusing on past optimal actions.
C.Exploration ensures that the Q-learning model only focuses on the optimal policy.
D.Exploration helps the model to learn about possible states and potential actions by occasionally choosing random actions.
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标准答案
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思路分析
When considering how exploration affects Q-learning, it's useful to parse what exploration is trying to accomplish in reinforcement learning contexts. Option 1: 'Exploration rapidly decreases the learning rate (α) to avoid overfitting the model.' This is not a standard or correct description of exploration. The learning rate α controls how new information updates the Q-values, not the exploration strategy itself,......Login to view full explanation

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Shown is the Q Actor-Critic (QAC) function, with line numbers. 1. Initialise 𝑠 , 𝜃 2. Sample 𝑎 ∼ 𝜋 𝜃 3. for each step do 4.      Sample reward 𝑟 = 𝑅 𝑠 𝑎 ; sample transition 𝑠 ′ ∼ 𝑃 𝑠 , ⋅ 𝑎 5.      Sample action 𝑎 ′ ∼ 𝜋 𝜃 ( 𝑠 ′ , 𝑎 ′ ) 6.      𝛿 = 𝑟 + 𝛾 𝑄 𝑤 ( 𝑠 ′ , 𝑎 ′ ) − 𝑄 𝑤 ( 𝑠 , 𝑎 ) 7.      𝜃 ← 𝜃 + 𝛼 ∇ 𝜃 𝑙 𝑜 𝑔 𝜋 𝜃 ( 𝑠 , 𝑎 ) 𝑄 𝑤 ( 𝑠 , 𝑎 ) 8.      𝑤 ← 𝑤 + 𝛽 𝛿 𝜙 ( 𝑠 , 𝑎 ) 9.      𝑎 ← 𝑎 ′ , 𝑠 ← 𝑠 ′ 10. end for Which of the following statements is true (can be more than one)?

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