Research Article
Space Searching Algorithms Used by Fungi
@ARTICLE{10.4108/eai.3-12-2015.2262591, author={Elitsa Asenova and Eileen Fu and Dan Nicolau Jr and Hsin-Yu Lin and Dan Nicolau}, title={Space Searching Algorithms Used by Fungi}, journal={EAI Endorsed Transactions on Collaborative Computing}, volume={2}, number={9}, publisher={ACM}, journal_a={CC}, year={2016}, month={5}, keywords={maze searching, natural algorithms, biomimetics, microfluidics}, doi={10.4108/eai.3-12-2015.2262591} }- Elitsa Asenova
Eileen Fu
Dan Nicolau Jr
Hsin-Yu Lin
Dan Nicolau
Year: 2016
Space Searching Algorithms Used by Fungi
CC
EAI
DOI: 10.4108/eai.3-12-2015.2262591
Abstract
Experimental studies have shown that fungi use a natural program for searching the space available in micro-confined networks, e.g., mazes. This natural program, which comprises two subroutines, i.e., collision-induced branching and directional memory, has been shown to be efficient compared with the suppressing one, or both subroutines. The present contribution compares the performance of the fungal natural program against several standard space searching algorithms. It was found that the fungal natural algorithm consistently outperforms Depth-First-Search (DFS) algorithm, and although it is inferior to informed algorithms, such as A*, this under-performance does not increase importantly with the increase of the size of the maze. These findings encourage a systematic effort to harvest the natural space searching algorithms used by microorganisms, which, if efficient, can be reverse-engineered for graph and tree search strategies.
Copyright © 2015 D. Nicolau et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
