dc.contributor.author | Harder, Malte | |
dc.contributor.author | Polani, D. | |
dc.date.accessioned | 2015-06-03T07:51:09Z | |
dc.date.available | 2015-06-03T07:51:09Z | |
dc.date.issued | 2013-05-01 | |
dc.identifier.citation | Harder , M & Polani , D 2013 , ' Self-organizing particle systems ' , Advances in Complex Systems , vol. 16 , no. 2-3 , 1250089 . https://doi.org/10.1142/S0219525912500890 | |
dc.identifier.issn | 0219-5259 | |
dc.identifier.other | PURE: 8615055 | |
dc.identifier.other | PURE UUID: 078869b7-a030-4293-9f32-ed43161b68a2 | |
dc.identifier.other | Scopus: 84880380187 | |
dc.identifier.other | ORCID: /0000-0002-3233-5847/work/86098035 | |
dc.identifier.uri | http://hdl.handle.net/2299/15993 | |
dc.description | This is a pre-copyedited, author-produced PDF of an article accepted for publication in Advances in Complex Systems following peer review. The version of record, Malte Harder and Daniel Polani, ‘Self-organizing particle systems’, Advs. Complex Syst. 16, 1250089, published October 22, 2012, is available online via doi: https://doi.org/10.1142/S0219525912500890 Published by World Scientific Publishing. | |
dc.description.abstract | The self-organization of cells into a living organism is a very intricate process. Under the surface of orchestrating regulatory networks there are physical processes which make the information processing possible, that is required to organize such a multitude of individual entities. We use a quantitative information theoretic approach to assess self-organization of a collective system. In particular, we consider an interacting particle system, that roughly mimics biological cells by exhibiting differential adhesion behavior. Employing techniques related to shape analysis, we show that these systems in most cases exhibit self-organization. Moreover, we consider spatial constraints of interactions, and additionaly show that particle systems can self-organize without the emergence of pattern-like structures. However, we will see that regular pattern-like structures help to overcome limitations of self-organization that are imposed by the spatial structure of interactions. | en |
dc.format.extent | 24 | |
dc.language.iso | eng | |
dc.relation.ispartof | Advances in Complex Systems | |
dc.subject | information theory | |
dc.subject | morphogenesis | |
dc.subject | Self-organization | |
dc.subject | Control and Systems Engineering | |
dc.subject | General | |
dc.title | Self-organizing particle systems | en |
dc.contributor.institution | School of Computer Science | |
dc.contributor.institution | Science & Technology Research Institute | |
dc.contributor.institution | Centre for Computer Science and Informatics Research | |
dc.contributor.institution | Adaptive Systems | |
dc.description.status | Peer reviewed | |
rioxxterms.versionofrecord | https://doi.org/10.1142/S0219525912500890 | |
rioxxterms.type | Journal Article/Review | |
herts.preservation.rarelyaccessed | true | |