Problem-solving terminology in AI: What is the term for the judgmental, experience-based, or commonsense component of problem solving that guides search and decision making?

Introduction / Context:
Artificial intelligence and cognitive psychology distinguish between algorithmic procedures that guarantee optimal solutions and heuristic methods that trade optimality for speed and practicality, drawing on rules of thumb and domain intuition.

Given Data / Assumptions:

• We focus on the ‘‘commonsense’’ or ‘‘judgmental’’ aspect of problem solving.
• Emphasis is on guidance, shortcuts, and plausible strategies rather than exhaustive search.
• Term is widely used in AI, operations research, and decision science.

Concept / Approach:
A heuristic is a strategy or rule of thumb that helps find satisfactory solutions efficiently. Heuristics guide search (e.g., A*'s admissible heuristics), prune options, and prioritize actions when computation or information is limited.

Step-by-Step Solution:

Verification / Alternative check:
Standard AI textbooks define heuristics exactly in this manner—as informed, non-guaranteed strategies that reduce search effort.

Why Other Options Are Wrong:

• ‘‘Analytical’’ and ‘‘critical’’ describe reasoning styles, not specific guidance rules.
• ‘‘Value based’’ refers to preference modeling, not commonsense shortcuts.

Common Pitfalls:
Assuming heuristics always produce optimal answers; they aim for ‘‘good enough’’ quickly, balancing accuracy and cost.

Final Answer:
Heuristic