Define and monitor the reward signal: Which control directly | AIGP
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Define and monitor the reward signal: Which control directly fits this learning approach?

AIGP Understanding the Foundations of AI Governance Medium

Feedback about action consequences indicates reinforcement learning, requiring reward design and monitoring.

The question

A factory system changes inspection behavior using operator feedback about whether its actions improved outcomes. Safety, security, data-quality, and documentation prerequisites are already satisfied. Which control directly fits this learning approach?

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  1. Use clustering to discover inspection patterns.
    Clustering discovers structure without representing the feedback signal that guides behavior toward better outcomes.
  2. Document customer-facing explanations for every inspection result.
    Explanations may support transparency, but they do not control the feedback signal driving this learning approach.
  3. Add fixed target labels to training cases.
    Fixed labels support supervised learning, but the scenario describes feedback about consequences of actions.
  4. Define and monitor the reward signal. ✓
    Reinforcement learning uses feedback about the consequences of actions. Defining and monitoring the reward signal helps align adaptation with the manufacturing objective.
The trap
Distinguish target labels from feedback about action consequences; the latter indicates reinforcement learning.

How to remember it

Feedback about action consequences indicates reinforcement learning, requiring reward design and monitoring.

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