Space Searching Algorithms Used by Fungi

• Main Authors: Elitsa Asenova, Eileen Fu, Dan Nicolau Jr, Hsin-Yu Lin, Dan Nicolau
• Format: Article
• Language: English
• Published: European Alliance for Innovation (EAI) 2016-12-01
• Series: EAI Endorsed Transactions on Collaborative Computing
• Subjects: maze searching; natural algorithms; biomimetics; microfluidics
• Online Access: http://eudl.eu/doi/10.4108/eai.3-12-2015.2262591

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.