Intelligence: Maze-solving by an amoeboid organism

@article{Nakagaki2000IntelligenceMB,
  title={Intelligence: Maze-solving by an amoeboid organism},
  author={Toshiyuki Nakagaki and Hiroyasu Yamada and {\'A}gota T{\'o}th},
  journal={Nature},
  year={2000},
  volume={407},
  pages={470-470}
}
The plasmodium of the slime mould Physarum polycephalum is a large amoeba-like cell consisting of a dendritic network of tube-like structures (pseudopodia). It changes its shape as it crawls over a plain agar gel and, if food is placed at two different points, it will put out pseudopodia that connect the two food sources. Here we show that this simple organism has the ability to find the minimum-length solution between two points in a labyrinth. 

Smart behavior of true slime mold in a labyrinth.

Searching strategy of slime mold and its mathematical model

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It is found that slime mold can change the searching strategy by observing the slime mold in the branching lanes and a mathematical model of physarum expanding is made to explain this behavior.

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How the plasmodium generates new motility and morphology is investigated, and it is found that there are allometric relationships between the cell volume and morphology, and between cell size and cell motility.

Fast shortest path optimization inspired by shuttle streaming of Physarum polycephalum

This work has proposed mathematical models to mimic the intelligent foraging behavior that can be used to find the shortest path between two points of a graph and found that the convergence of the proposed two versions, Physarum Optimization with Shuttle Streaming and POSS with mutation, are 40-11650 times faster when compared with the currently availablephysarum Solver method.

Observation of Autonomous Behavioral Selection in Physarum Plasmodium

This study focused on the phenomenon in which a plasmodium trapped in a closed space surrounded by repellent substances escapes from the field by changing its own behavior rules and demonstrated that this phenomenon is bio-computationally important in that it may enable the implementation of biological characteristics in computing.

Milestone V

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Adaptive Path-Finding and Transport Network Formation by the Amoeba-Like Organism Physarum

Some factors that can affect path-finding through networks are reported here to help understand more generally how the organism tries to establish an optimal set of paths in more complex environments and how this behaviour can be captured in relatively simple algorithms.

Diversity in the Chemotactic Behavior of Physarum Plasmodium Induced by Bi-modal Stimuli

The diversity of the behaviors of the plasmodium and how these behaviors may arise is demonstrated and a simulation model of the behavior was constructed that replicated the behavioral diversity with a simple combination of molecular apparatuses.

Insights into Information Processing by the Single Cell Slime Mold Physarum Polycephalum

A simple explanation for the finding that a simple single-celled organism can traverse a maze near optimally and a computational model based on decision trees and ant algorithmics are presented.

Path Planning with Slime Molds: A Biology-Inspired Approach

An Artificial Plasmodium Algorithm (APA) mimicked a contraction wave of a plas modium of physarum polucephalum to solve mazes and it is confirmed that the APA can solve the mazes.
...

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