--- abstract: 'The idea of a “memetic” spread of solutions through a human culture in parallel to their development is applied as a distributed approach to learning. Local parts of a problem are associated with a set of overlappingt localities in a space and solutions are then evolved in those localites. Good solutions are not only crossed with others to search for better solutions but also they propogate across the areas of the problem space where they are relatively successful. Thus the whole population co-evolves solutions with the domains in which they are found to work. This approach is compared to the equivalent global evolutionary computation approach with respect to predicting the occcurence of heart disease in the Cleveland data set. It greatly outperforms the global approach, but the space of attributes within which this evolutionary process occurs can effect its efficiency.' altloc: - http://cfpm.org/cpmrep141.html chapter: ~ commentary: ~ commref: ~ confdates: 'April, 2005' conference: AISB symposium on Socially Inspired Computing confloc: 'University of Hertfordshire, Hatfield, UK' contact_email: ~ creators_id: [] creators_name: - family: Edmonds given: Bruce honourific: '' lineage: '' date: 2005 date_type: published datestamp: 2005-04-21 department: ~ dir: disk0/00/00/42/65 edit_lock_since: ~ edit_lock_until: ~ edit_lock_user: ~ editors_id: [] editors_name: [] eprint_status: archive eprintid: 4265 fileinfo: /style/images/fileicons/application_pdf.png;/4265/1/ulgtsdl.pdf|/style/images/fileicons/text_html.png;/4265/2/ulgtsdl.html full_text_status: public importid: ~ institution: ~ isbn: ~ ispublished: pub issn: ~ item_issues_comment: [] item_issues_count: 0 item_issues_description: [] item_issues_id: [] item_issues_reported_by: [] item_issues_resolved_by: [] item_issues_status: [] item_issues_timestamp: [] item_issues_type: [] keywords: 'meme, gossip, cultural diffusion, local learning, machine learning, evolutionary algorithms, genetic programming, heart disease' lastmod: 2011-03-11 08:55:59 latitude: ~ longitude: ~ metadata_visibility: show note: ~ number: ~ pagerange: 127-134 pubdom: FALSE publication: ~ publisher: AISB refereed: TRUE referencetext: |- Aha, D. and Kibler, D. 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Parallel Problem Solving from Nature PPSN V 5th Internation Conference, Springer, LNAI ?? Wolpert, D. H. and Macready, W. G. No Free Lunch Theorems for Optimization, IEEE Transactions on Evolutionary Computation 1 (1997): 67–82. Wright, S. (1932) The roles of mutation, inbreeding, crossbreeding and selection in evolution. In Proceedings of the 6th International Congress of Genetics, vl. 1, 356-366. relation_type: [] relation_uri: [] reportno: ~ rev_number: 14 series: ~ source: ~ status_changed: 2007-09-12 16:57:51 subjects: - comp-sci-mach-learn - bio-eco - socsim succeeds: ~ suggestions: ~ sword_depositor: ~ sword_slug: ~ thesistype: ~ title: Using Localised ‘Gossip’ to Structure Distributed Learning type: confpaper userid: 192 volume: ~