How AI Systems Work – Practical Foundations for Modern Learners
Lesson 2: Search, Choices, and Better Paths
Lesson Objectives
By the end of this lesson, students should be able to:
- Explain search as choosing a path through possible states.
- Compare blind trial-and-error with guided search.
- Use simple heuristics to narrow a problem.
Lesson Content
Many AI problems start with a simple question: "What should happen next?" A system may need to find a route, choose a sequence of steps, arrange a schedule, solve a puzzle, select a recommendation, or decide which option is most likely to help.
Search means exploring possible choices. Some choices lead nowhere. Some choices look promising. A heuristic is a practical rule of thumb that helps the system focus on better options sooner. Humans use heuristics constantly. If you are looking for your keys, you do not inspect every inch of the house equally. You check likely places first.
AI search can fail when the problem is too large, the goal is unclear, or the shortcut rule points in the wrong direction. That is why good problem framing matters.
Enroll to continue this lesson.
The preview above shows the lesson objectives and opening lesson content. Enroll to view the full lesson, complete the practice work, and take the lesson quiz.