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How Slime Moulds Solve Mazes and Find Efficient Routes

In a classic maze experiment, Physarum polycephalum reorganized its tube network to connect two food sources by a shorter route. Here’s how to interpret the result without mistaking adaptive growth for conscious planning.
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Physarum polycephalum can form a short connection between two food sources in a maze. In a classic 2000 experiment, the slime mould spread through a labyrinth and then reorganized its network of tubes; the prominent connection followed the shorter route. That is adaptive network formation—not evidence that the organism consciously plans or understands a route.

What happened in the maze experiment?

In a study published on 28 September 2000, Toshiyuki Nakagaki, Hiroyasu Yamada and Ágota Tóth placed the plasmodium of Physarum polycephalum in a maze with food at two locations. The plasmodium—a large, changing, amoeba-like mass—spread across the agar gel and extended tube-like structures as it foraged. Over time, a prominent tube connected the food sites by the maze’s minimum-length route. The authors described the result as finding a “minimum-length solution between two points in a labyrinth.” Nature’s paper abstract and a later study’s summary of the experiment describe this route-finding outcome.

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The result was a change in the organism’s physical network, not a demonstration of a slime mould navigating with a map or deliberately comparing paths as a human would.

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How does it end up with the shorter route?

The key is to think of the maze as a changing network rather than a puzzle the organism consciously solves. The plasmodium initially explores and forms connections. As it forages, its tube network changes: a connection along the shorter route remains prominent, while less useful alternatives do not persist in the same way. The experiment records the resulting network; it does not establish human-like intention or a mental plan.

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Mathematical studies model tube networks as flows and examine how adaptive changes can make a network converge on a shortest path under the model’s assumptions. Those analyses help explain how route selection can arise from network dynamics, but they are distinct from the laboratory observation of the maze result. See the 2012 paper, “Physarum can compute shortest paths”, for this modeling perspective.

How much shorter was the route?

In the route comparison shown in the 2000 paper, the selected route α2 was about 22% shorter than the alternative α1. That figure applies to those two paths in that particular published comparison; it is not a general success rate or a claim that slime moulds shorten routes by 22% in every maze. The paper’s route-length figure gives the comparison.

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What does the maze result have to do with transport networks?

Related work explored whether the same broad principle of adaptive network formation could inform infrastructure design. A 2010 study compared networks formed by Physarum with Tokyo’s rail system across efficiency, fault tolerance and cost, and presented a biologically inspired mathematical model for designing adaptive networks. The comparison is about network properties and design ideas; the maze experiment did not rebuild Tokyo’s rail system, and the organism was not consciously engineering transport infrastructure. See the study’s PubMed record.

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What the experiment does—and does not—show

  • It shows: a living tube network can reorganize into a short connection between two food locations in a labyrinth.
  • It does not show: conscious reasoning, a mental map, or a general guarantee that the organism will find the shortest path in every maze.
  • It suggests: adaptive biological networks can inspire mathematical approaches to routing and infrastructure design, which need to be assessed separately from the organism’s laboratory behavior.

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