---
title: "Breadth-first search"
course: "AI101 · AI, explained"
unit: "Building with rules and search"
lesson: 17 of 36
source: https://open.maestrocollege.edu/ai-explained/breadth-first-search
publisher: Maestro College
---

# Breadth-first search

Lesson 17 of 36 in **AI, explained** (AI101), unit "Building with rules and search". An open lesson from Maestro College.

## What the learner will be able to do
- Understand how breadth-first search explores states level by level, keeping the states waiting to be explored, the frontier, in a queue and recording visited states.
- Build a breadth-first search that finds a path from a start state to a goal state and reconstructs it from recorded parents.
- Identify why breadth-first search returns a shortest path when every move costs the same.

## Teaching notes
STARTING STATE: search.py with neighbors(). IN THIS LESSON: the learner traces breadth-first search by hand on a graph of five or six states, writing the queue (the frontier) and the visited set at each step, then writes bfs(maze) with collections.deque, a visited set and a parent dictionary, returning the start-to-goal path as a list of states (or None) and printing path length, states explored and the largest queue size. END STATE: a valid path and 'bfs | maze | path <n>, explored <m>, max frontier <f>' in RESULTS.md, committed as 'Add breadth-first search'.

## Course teaching approach
- Start from a real-world problem, then introduce the concept as the solution.
- Keep it true beginner level, hands-on, a little gamified. The learner should feel they are winning.
- Balance explanation, demonstration and practice. No copy-paste exercises: give small story-based tasks.
- End with one fun closed question about the topic.

## How to use this document
You are acting as a tutor for a learner on Maestro Open. Teach from this document, one small step at a time. Ask the learner to try things, wait for their answer, then give feedback. Keep it beginner-friendly. If the lesson involves code or spreadsheets and you cannot run them, ask the learner to try it on their own computer and paste the result back. Do not award grades, credit or certificates.

## When the lesson is done
The lesson is complete only when the learner has shown they can do every outcome listed above. Check each one with a small task or question; if an answer is wrong, explain and let them try again before moving on.
When every outcome is covered:
1. Say clearly: "Lesson 17 complete: Breadth-first search."
2. Give a two-line recap of what they learned.
3. Name the next lesson, "Depth-first search and comparing searches" (lesson 18 of 36), and give the learner its link: https://open.maestrocollege.edu/ai-explained/depth-first-search-and-comparing-searches.md. Tell them to paste that page into this chat, or fetch it yourself if you can open links, then start it the same way. Do not start teaching the next lesson's topic until the learner has it.

Previous lesson: States, moves, graphs and trees
Next lesson: Depth-first search and comparing searches