In reinforcement learning, what is the term for the entity that makes decisions?

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Multiple Choice

In reinforcement learning, what is the term for the entity that makes decisions?

In reinforcement learning, the decision-maker is the agent. The agent sits in an environment and, at each step, observes the current state, chooses an action according to its policy, and then receives a reward along with the next state. The policy is the rule the agent uses to pick actions, but it’s the agent that actually acts in the environment. The environment provides the states and rewards and determines how the state changes in response to the agent’s actions, while the reward gives feedback used to improve future decisions. The agent’s goal is to learn a policy that maximizes the expected cumulative reward over time.

In reinforcement learning, the decision-maker is the agent. The agent sits in an environment and, at each step, observes the current state, chooses an action according to its policy, and then receives a reward along with the next state. The policy is the rule the agent uses to pick actions, but it’s the agent that actually acts in the environment. The environment provides the states and rewards and determines how the state changes in response to the agent’s actions, while the reward gives feedback used to improve future decisions. The agent’s goal is to learn a policy that maximizes the expected cumulative reward over time.

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