What is the exploration-exploitation trade-off in Reinforcement Learning?

Options

  • A. The agent must balance trying new actions with choosing actions that are already known to provide good rewards
  • B. The agent must always choose a completely random action
  • C. The agent must always repeat the first action it learns
  • D. The agent must avoid receiving rewards during learning
  • E. None of the above

Correct Answer (Detailed Explanation is Below)

A. The agent must balance trying new actions with choosing actions that are already known to provide good rewards

Detailed Explanation

The exploration-exploitation trade-off is a fundamental concept in Reinforcement Learning. Exploration means trying new actions to discover potentially better rewards, while exploitation means selecting actions that are already known to produce good rewards. A successful agent balances both.

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