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Questions and Answers
Which of the following is the goal of an RL agent?
Which of the following is the goal of an RL agent?
- To maximize their cumulative reward (correct)
- To minimize the amount of trial and error
- To minimize the amount of gradient descent
- To minimize the amount of information about their current state
What type of information is required to find an optimal policy for an RL problem?
What type of information is required to find an optimal policy for an RL problem?
- Information about the agent's past behavior (correct)
- Information about the agent's current state
- Information about the agent's expected reward
- Information about the agent's expected cumulative reward
What is the main computational approach used in reinforcement learning?
What is the main computational approach used in reinforcement learning?
- Gradient descent
- Trial and error
- Reward hypothesis
- Learning from action (correct)
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Study Notes
- Reinforcement learning is a computational approach of learning from action.
- Goal RL agents seek to maximize their expected cumulative reward, which is based on the reward hypothesis.
- There are two ways to find an optimal policy for an RL problem: by trial and error or by using a gradient descent algorithm.
- Both methods require information about the agent's past behavior and its current state.
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