cc 16(9): e5

Research Article

Space Searching Algorithms Used by Fungi

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  • @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
Elitsa Asenova1, Eileen Fu1, Dan Nicolau Jr2, Hsin-Yu Lin1, Dan Nicolau,*
  • 1: McGill University
  • 2: Queensland University of Technology
*Contact email: dan.nicolau@mcgill.ca

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.