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  Preliminaries for Distributed Natural Computing Inspired by the Slime Mold Physarum Polycephalum

Dirnberger, M. (2017). Preliminaries for Distributed Natural Computing Inspired by the Slime Mold Physarum Polycephalum. PhD Thesis, Universität des Saarlandes, Saarbrücken.

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Datensatz-Permalink: https://hdl.handle.net/11858/00-001M-0000-002D-DE4F-0 Versions-Permalink: https://hdl.handle.net/21.11116/0000-0001-8BD6-1
Genre: Hochschulschrift

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externe Referenz:
http://scidok.sulb.uni-saarland.de/volltexte/2017/6942/ (beliebiger Volltext)
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Grün
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http://scidok.sulb.uni-saarland.de/doku/lic_ohne_pod.php?la=de (Verlagsvertrag)
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 Urheber:
Dirnberger, Michael1, 2, Autor           
Mehlhorn, Kurt1, Ratgeber           
Grube, Martin3, Gutachter
Döbereiner, Hans-Günther3, Gutachter
Affiliations:
1Algorithms and Complexity, MPI for Informatics, Max Planck Society, ou_24019              
2International Max Planck Research School, MPI for Informatics, Max Planck Society, Campus E1 4, 66123 Saarbrücken, DE, ou_1116551              
3External Organizations, ou_persistent22              

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 Zusammenfassung: This doctoral thesis aims towards distributed natural computing inspired by the slime mold Physarum polycephalum. The vein networks formed by this organism presumably support efficient transport of protoplasmic fluid. Devising models which capture the natural efficiency of the organism and form a suitable basis for the development of natural computing algorithms is an interesting and challenging goal. We start working towards this goal by designing and executing wet-lab experi- ments geared towards producing a large number of images of the vein networks of P. polycephalum. Next, we turn the depicted vein networks into graphs using our own custom software called Nefi. This enables a detailed numerical study, yielding a catalogue of characterizing observables spanning a wide array of different graph properties. To share our results and data, i.e. raw experimental data, graphs and analysis results, we introduce a dedicated repository revolving around slime mold data, the Smgr. The purpose of this repository is to promote data reuse and to foster a practice of increased data sharing. Finally we present a model based on interacting electronic circuits including current controlled voltage sources, which mimics the emergent flow patterns observed in live P. polycephalum. The model is simple, distributed and robust to changes in the underlying network topology. Thus it constitutes a promising basis for the development of distributed natural computing algorithms.

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Sprache(n): eng - English
 Datum: 2017-07-312017-08-242017
 Publikationsstatus: Erschienen
 Seiten: XV, 193 p.
 Ort, Verlag, Ausgabe: Saarbrücken : Universität des Saarlandes
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: BibTex Citekey: dirnbergerphd17
URN: urn:nbn:de:bsz:291-scidok-69424
 Art des Abschluß: Doktorarbeit

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