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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/89565 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/89565 http://eprints.org/relation/ismediumThumbnailVersionOf https://pure.iiasa.ac.at/id/document/89565 89570 2 257591 document 89570 small.jpg image/png 4d4cbfba8782921f2ef805b346145fa3 MD5 1676 2020-02-24 08:52:33 https://pure.iiasa.ac.at/id/eprint/16310/6/small.jpg 16310 6 6 image/png other Thumbnails conversion from text to thumbnail_small en public

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/89565 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/89565 http://eprints.org/relation/issmallThumbnailVersionOf https://pure.iiasa.ac.at/id/document/89565 archive 353 disk0/00/01/63/10 2020-02-24 08:43:47 2021-08-27 17:32:39 2020-02-24 08:43:47 article show Park C. 9021 pub prog_eep System approach, Agent-based model, Elementary coordination, Circadian cycles, Collective structure One of the basic approaches in science views behavioral products as a process within a dynamic system. The mechanism might be seen as a representation of many instances of centralized control in real time. Many real systems, however, exhibit autonomy by denying statically treated mechanisms. This study addresses the issues related to the identification of dynamic systems and suggests how determining the basic principles of a collective structure may be the key to understanding complex behavioral processes. A fundamental model is derived to assess the advantages of this perspective using a basic methodology. The connection between perspective and technique demonstrates certain aspects within their actual context while also clearly including the framework of actual dynamic system identification. 2020-12-01 published 10.1186/s40294-019-0066-x 2940 public Complex Adaptive Systems Modeling 8 1 e2 TRUE 2194-3206 FALSE no info:eu-repo/semantics/article