Feedback is information about the gap between a result and its goal. An agent can use feedback to correct a step, choose another route, or ask a person for help.

Feedback Compares Result With Aim

A transition applies an event or result to the current state and selects a next state. Its preconditions and effects should be explicit enough to test.

A Transition Changes Graph State

An AI agent observes context, chooses an action, uses a model or tool, and updates what happens next. Its engineered identity lies in this loop and its boundaries, not in a chat-shaped interface.

AI Agent as a Goal-Directed Loop

A closed loop measures an outcome, compares it with a target, and changes the next action. Without a trustworthy measure, repeated self-critique may only reinforce the same error.

Closed-Loop Control Uses Measured Feedback

In this situation—a route planner learning that one suggested station is temporarily closed—which choice best applies “Feedback Compares Result With Aim”?

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