Optimal Fungal Space Searching Algorithms
Previous experiments have shown that fungi use an efficient natural algorithm for searching the space available for their growth in micro-confined networks, e.g., mazes. This natural "master" algorithm, which comprises two "slave" sub-algorithms, i.e., collision-induced branching and directional memory, has been shown to be more efficient than alternatives, with one, or the other, or both sub-algorithms turned off. In contrast, the present contribution compares the performance of the fungal natural algorithm against several standard artificial homologues. It was found that the space-searching fungal algorithm consistently outperforms uninformed algorithms, such as Depth-First-Search (DFS). Furthermore, while the natural algorithm is inferior to informed ones, such as A*, this under-performance does not importantly increase with the increase of the size of the maze. These findings suggest that a systematic effort of harvesting the natural space searching algorithms used by microorganisms is warranted and possibly overdue. These natural algorithms, if efficient, can be reverse-engineered for graph and tree search strategies.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2016 |
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| Erschienen: |
2016 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:15 |
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| Enthalten in: |
IEEE transactions on nanobioscience - 15(2016), 7 vom: 17. Okt., Seite 613-618 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Asenova, Elitsa [VerfasserIn] |
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| Links: |
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| Themen: |
Journal Article |
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| Anmerkungen: |
Date Completed 05.09.2017 Date Revised 22.12.2017 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1109/TNB.2016.2567098 |
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| funding: |
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NLM260427373 |
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| 520 | |a Previous experiments have shown that fungi use an efficient natural algorithm for searching the space available for their growth in micro-confined networks, e.g., mazes. This natural "master" algorithm, which comprises two "slave" sub-algorithms, i.e., collision-induced branching and directional memory, has been shown to be more efficient than alternatives, with one, or the other, or both sub-algorithms turned off. In contrast, the present contribution compares the performance of the fungal natural algorithm against several standard artificial homologues. It was found that the space-searching fungal algorithm consistently outperforms uninformed algorithms, such as Depth-First-Search (DFS). Furthermore, while the natural algorithm is inferior to informed ones, such as A*, this under-performance does not importantly increase with the increase of the size of the maze. These findings suggest that a systematic effort of harvesting the natural space searching algorithms used by microorganisms is warranted and possibly overdue. These natural algorithms, if efficient, can be reverse-engineered for graph and tree search strategies | ||
| 650 | 4 | |a Journal Article | |
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| 700 | 1 | |a Lin, Hsin-Yu |e verfasserin |4 aut | |
| 700 | 1 | |a Fu, Eileen |e verfasserin |4 aut | |
| 700 | 1 | |a Nicolau, Dan V |e verfasserin |4 aut | |
| 700 | 1 | |a Nicolau, Dan V |e verfasserin |4 aut | |
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