Case context: A learning algorithm produces a pilot trajectory. The team has a human pilot trajectory that performs better, but the team cannot show that the human trajectory is optimal.

Question: Decide whether the team can use the human trajectory for Optimization Verification and explain what the test can indicate.

Sample answer: Yes. The team can use the human trajectory as y* because it is superior to the current learning algorithm's trajectory, even though it is not known to be optimal. The resulting test can indicate whether improving the optimization algorithm or improving the scoring function is more promising.

Key points:

• The human trajectory is better than the current algorithm's output.
• Proven optimality is unnecessary.
• The human trajectory can serve as y*.
• The test compares the promise of improving optimization and scoring.

Rubric: The response should approve using the human trajectory based on its superiority, avoid claiming that it is optimal, and identify the optimization-versus-scoring decision supported by the test.