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Why some people mow a lawn better than others

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Why This Matters

This study highlights how humans excel at solving complex path planning tasks, often approaching optimal solutions better than computers in certain scenarios. Understanding human strategies in such problems can inform the development of more efficient algorithms for robotics, automation, and logistics, ultimately benefiting consumers and industries reliant on efficient route planning.

Key Takeaways

Give it a try. How efficiently can you mow this lawn?

You’ve probably done something like mow a lawn or vacuum a rug hundreds of times without thinking much about it. Some part of your brain works out a route that’s usually good enough to get the job done. People are actually pretty good at this, and better than you’d guess for a problem that is hard for computers. We wanted to see it for ourselves, so we built a lawn and asked people to mow it.

You skipped the game, so here is just the optimal path. Is this what you would’ve done? An Optimal path Replay

A few weeks ago, 30,954 people mowed the same lawn. This is what their paths looked like.

player id: ( moves)

Many came close to the optimal path. 52% of people came within five moves of the best possible path, and 16% did it perfectly.

Many different approaches, yet similar, pretty good outcomes. Only 49 squares need to be covered, but people found 14,589 different ways to do it. Despite all that variety, the median person still hit 91% efficiency (within 5 moves).

For this small lawn, there are 12 different perfect solutions and people found them all.

But what were you actually solving?

Finding the best path through the squares is a classic computer science problem. No, don’t leave! We promise this won’t get too wonky.

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