--- abstract: 'Various research initiatives try to utilize the operational principles of organisms and brains to develop alternative, biologically inspired computing paradigms and artificial cognitive systems. This article reviews key features of the standard method applied to complexity in the cognitive and brain sciences, i.e. decompositional analysis or reverse engineering. The indisputable complexity of brain and mind raise the issue of whether they can be understood by applying the standard method. Actually, recent findings in the experimental and theoretical fields, question central assumptions and hypotheses made for reverse engineering. Using the modeling relation as analyzed by Robert Rosen, the scientific analysis method itself is made a subject of discussion. It is concluded that the fundamental assumption of cognitive science, i.e. complex cognitive systems can be analyzed, understood and duplicated by reverse engineering, must be abandoned. Implications for investigations of organisms and behavior as well as for engineering artificial cognitive systems are discussed.' altloc: [] chapter: ~ commentary: ~ commref: ~ confdates: ~ conference: ~ confloc: ~ contact_email: ~ creators_id: - schierwa@uni-leipzig.de creators_name: - family: Schierwagen given: Andreas honourific: Prof. lineage: '' date: 2012-03-01 date_type: published datestamp: 2012-11-25 12:34:51 department: ~ dir: disk0/00/00/87/29 edit_lock_since: ~ edit_lock_until: 0 edit_lock_user: ~ editors_id: [] editors_name: [] eprint_status: archive eprintid: 8729 fileinfo: /8729/1.hassmallThumbnailVersion/2012_Schierwagen_Rev_Engn.pdf;/8729/1/2012_Schierwagen_Rev_Engn.pdf full_text_status: public importid: ~ institution: ~ isbn: ~ ispublished: pub issn: ~ item_issues_comment: [] item_issues_count: ~ item_issues_description: [] item_issues_id: [] item_issues_reported_by: [] item_issues_resolved_by: [] item_issues_status: [] item_issues_timestamp: [] item_issues_type: [] keywords: " Brain\r\n Cognition\r\n Capacity\r\n Decompositional analysis\r\n Localization\r\n Linearity\r\n Modularization\r\n Column concept\r\n Reverse engineering\r\n Complex systems\r\n Modeling relation\r\n\r\n" lastmod: 2013-02-18 15:12:36 latitude: ~ longitude: ~ metadata_visibility: show note: ~ number: 1 pagerange: 141-150 pubdom: TRUE publication: Natural Computing publisher: Springer refereed: TRUE referencetext: "1.\tArbib M, Érdi P, Szenthágothai J (1997) Neural organization: structure, function and dynamics. 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Proc Biennial Meeting Philos Sci Ass 1972:67–86 \r\n\r\n" relation_type: [] relation_uri: [] reportno: ~ rev_number: 14 series: ~ source: ~ status_changed: 2012-11-25 12:34:51 subjects: - cog-psy - comp-neuro-sci - phil-sci succeeds: ~ suggestions: ~ sword_depositor: ~ sword_slug: ~ thesistype: ~ title: On Reverse Engineering in the Cognitive and Brain Sciences type: journalp userid: 18431 volume: 11