eprintid: 2097
rev_number: 6
eprint_status: archive
userid: 6
dir: disk0/00/00/20/97
datestamp: 2014-01-20 10:23:48
lastmod: 2014-01-20 10:23:48
status_changed: 2014-01-20 10:23:48
type: article
metadata_visibility: show
creators_name: Quattrociocchi, Walter
creators_name: Latorre, Daniela
creators_name: Lodi, Elena
creators_name: Nanni, Mirco
creators_id: walter.quattrociocchi@imtlucca.it
creators_id: 
creators_id: 
creators_id: 
title: Dealing with Interaction for Complex Systems Modelling and Prediction
ispublished: pub
subjects: QA
subjects: QA75
divisions: CSA
full_text_status: none
abstract: The increasing complexity of problems in the context of system modeling is leading to a new epistemological approach able to provide a representation which allows from one hand, to model complex phenomena with the support of mathematical and computational instruments, and on the other hand able to capture the global system description. In this article is presented a methodology for complex dynamical systems modeling which is an extension of the supervised learning paradigm. The theoretical aspects of our methodology are introduced and then two different and heterogeneous case studies are presented.
date: 2010
date_type: published
publication: International journal of artificial life research
volume: 1
number: 1
publisher: IGI Global
pagerange: 1-11
id_number: doi:10.4018/jalr.2010102101
refereed: TRUE
issn: 1947-3087
official_url: http://dx.doi.org/10.4018/jalr.2010102101
citation:   Quattrociocchi, Walter and Latorre, Daniela and Lodi, Elena and Nanni, Mirco  Dealing with Interaction for Complex Systems Modelling and Prediction.  International journal of artificial life research, 1 (1).  pp. 1-11.  ISSN 1947-3087      (2010)