DAA · Learn by doing

Maze Intelligence Visualizer

Scroll through the story — then tap simulations before you ever open the labyrinth.

01

What is a maze?

A maze is a network of choices. Each step commits you to a corridor; dead ends force retreat. Games teach intuition — algorithms teach exactly how escape is computed.

02

Maze as graph

Every walkable cell is a node; every legal step is an edge. Solving the maze = finding a route in that graph — from START to EXIT.

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Hover the highlighted algorithm names to see queue, stack, and priority queue in motion.

03

Meet BFS

Breadth First Search

Explores in rings. A queue guarantees the shortest hop-count path when edges cost the same.

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04

Meet DFS

Depth First Search

Dives deep first. Uses a stack — watch backtracking when paths dead-end.

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05

Meet Dijkstra

Dijkstra

Each corridor has a cost. A priority queue expands the cheapest frontier first.

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Algorithm speed comparison

The same miniature maze runs BFS (left) and DFS (right) side by side. Drag the slider to change step delay — BFS grows in layers while DFS snakes and backtracks.

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BFS
DFS
06

Try algorithm yourself

Click cells to place START then EXIT. Run any solver — instant visualization on a living maze.

First click: start · Second: exit

Ready?

You have touched queues, stacks, costs, and side-by-side rhythm — enter the full labyrinth when you choose.