Large-Scale Simulations for Complex Adaptive Systems with Application to Biological Domains

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dc.contributor.authorGuo, Donghangen
dc.contributor.committeechairSantos, Eunice E.en
dc.contributor.committeememberSantos, Eugene Jr.en
dc.contributor.committeememberArthur, James D.en
dc.contributor.committeememberRibbens, Calvin J.en
dc.contributor.committeememberLin, Taoen
dc.contributor.departmentComputer Scienceen
dc.date.accessioned2014-03-14T20:08:07Zen
dc.date.adate2008-03-13en
dc.date.available2014-03-14T20:08:07Zen
dc.date.issued2007-12-12en
dc.date.rdate2008-03-13en
dc.date.sdate2008-03-09en
dc.description.abstractModeling or simulating Complex Adaptive Systems (CASs) is both important and challenging. As the name suggests, CASs are systems consisting of large numbers of interacting adaptive compartments. They are studied across a wide range of disciplines and have unique properties. They model such systems as multicellular organisms, ecosystems, social networks, and many more. They are complex, in the sense that they are dynamical, nonlinear, and heterogeneous systems that cannot be simply scaled up/down. However, they are self-organized, in the sense that they can evolve into specific structures/patterns without guidance from outside sources. Modeling/Simulating CASs is challenging, not only because of the high complexity, but also because of the difficulty in explaining the underlying mechanism behind self-organization. The goal of this research is to provide a modeling framework as well as a simulation platform to advance the study of CASs. We argue that there are common principles behind self-organization processes of different systems across different domains. We explore, analyze, and perform experiments into these principles. We propose and implement modeling templates such as short-term and long-term adaptivity. We incorporate techniques from systems theory, employing computing paradigms, including multi-agent system and asynchronous message passing. We also consider an application from the biological domain to model and simulate under our framework, treating it as a CAS for validation purposes.en
dc.description.degreePh. D.en
dc.identifier.otheretd-03092008-221211en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-03092008-221211/en
dc.identifier.urihttp://hdl.handle.net/10919/26403en
dc.publisherVirginia Techen
dc.relation.haspartdissertation.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectAdaptivityen
dc.subjectSelf-Organizationen
dc.subjectMulti-Agent Systemen
dc.subjectComplex Adaptive Systemen
dc.subjectDictyostelium Discoideumen
dc.subjectInteractionen
dc.titleLarge-Scale Simulations for Complex Adaptive Systems with Application to Biological Domainsen
dc.typeDissertationen
thesis.degree.disciplineComputer Scienceen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en

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