Part 8/12:
I emphasized explainability, ensuring that the AI not only chooses an action but also justifies it. For example, based on the scenario, the AI inferred that the most effective approach might be to find the truck driver or to arrange for towing, depending on context.
Refinements improved the AI’s ability to infer causality and predict outcomes, moving from mere restatement to deep analysis of the problem.
Integrating the Agent Model: Who or What Am I?
A key insight was the importance of defining the system's agent model — a representation of identity, capabilities, and goals. For example, I configured the AI as a humanoid robot tasked primarily with assisting a company president, with secondary goals like profit maximization and safety.