B-TIER technique
Pathfinding algorithms explained — brute force vs flood fill
100k ft — What is this?
Pathfinding algorithms explained — brute force vs flood fill
50k ft — Why care?
@sanctity.ai reshare of a Veritasium clip explaining pathfinding (brute force, flood fill, backtracking) using a mouse-in-maze analogy. Teaching reference.
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1k ft — Deep-dive / try it
How do Pathfinder algorithms work?
• Imagine a mouse navigating a maze, searching for cheese.
• It could use a brute force approach, trying every path until it finds the goal. Effective but not efficient.
• Or, it could use a flood fill algorithm, exploring multiple routes simultaneously, ensuring it finds the shortest path quickly.
• Dead ends? The mouse backtracks, learning and adapting its strategy.
• Algorithms work similarly: they evaluate different paths, learn from failures, and optimize to reach the best solution efficiently.
• This process mirrors how your GPS finds the quickest route or how AI predicts outcomes.
Algorithms aren’t just about getting to the end—they’re about finding the smartest way to get there.
Video credit: @veritasium
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Transcript excerpt
Why does a simple computer mouse maze race burn out the CPUs of all contestants? The rules of the race are straightforward. Guide the computer mouse through the maze in the shortest time possible to reach the endpoint. Initially, most people directed the computer mouse to follow along one edge of the maze straight to the endpoint. However, this strategy fails when the endpoint is placed in the center of the maze, causing the computer mouse to continuously circle the outermost layer. Subsequent contestants developed a depth-first-search strategy choosing a direction at each intersection and returning to the intersection to try another path when encountering a dead end or loop. While this method allows the computer mouse to explore deeper into the maze, it only backtracks when there are no paths left and it doesn't necessarily find the shortest route. The contestants then improve the strategy to a breadth-first-search, trying all paths at each intersection. After marking all the intersections on the second layer, they would proceed to the next exploration and repeat the process. Although this method can find the shortest path, such thorough searching wastes a lot of time. What you're seeing now is the most commonly used flood-fill-search strategy. If the maze had no walls, the computer mouse would draw the shortest route. When encountering a wall, it marks it and assumes the rest of the area is still blank, recalculating and planning the route until reaching the endpoint. This…