AI and Art
In the context of reinforcement learning, actions are the specific choices or moves that an agent can make in an environment to achieve a desired outcome. These actions are crucial because they determine how the agent interacts with the environment and can lead to different rewards or penalties based on their effectiveness. The goal of reinforcement learning is to learn a policy that maximizes cumulative rewards through the selection of optimal actions over time.
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