Relevant bibliographies by topics / Complex and adaptive system

Academic literature on the topic 'Complex and adaptive system'

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Published: 14 March 2023

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Journal articles on the topic "Complex and adaptive system"

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Oughton, Edward J., Will Usher, Peter Tyler, and Jim W. Hall. "Infrastructure as a Complex Adaptive System." Complexity 2018 (November 4, 2018): 1–11. http://dx.doi.org/10.1155/2018/3427826.

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National infrastructure systems spanning energy, transport, digital, waste, and water are well recognised as complex and interdependent. While some policy makers have been keen to adopt the narrative of complexity, the application of complexity-based methods in public policy decision-making has been restricted by the lack of innovation in associated methodologies and tools. In this paper we firstly evaluate the application of complex adaptive systems theory to infrastructure systems, comparing and contrasting this approach with traditional systems theory. We secondly identify five key theoretical properties of complex adaptive systems including adaptive agents, diverse agents, dynamics, irreversibility, and emergence, which are exhibited across three hierarchical levels ranging from agents, to networks, to systems. With these properties in mind, we then present a case study on the development of a system-of-systems modelling approach based on complex adaptive systems theory capable of modelling an emergent national infrastructure system, driven by agent-level decisions with explicitly modelled interdependencies between energy, transport, digital, waste, and water. Indeed, the novel contribution of the paper is the articulation of the case study describing a decade of research which applies complex adaptive systems properties to the development of a national infrastructure system-of-systems model. This approach has been used by the UK National Infrastructure Commission to produce a National Infrastructure Assessment which is capable of coordinating infrastructure policy across a historically fragmented governance landscape spanning eight government departments. The application will continue to be pertinent moving forward due to the continuing complexity of interdependent infrastructure systems, particularly the challenges of increased electrification and the proliferation of the Internet of Things.
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Smith, Richard M., and Mark A. Bedau. "Is Echo a Complex Adaptive System?" Evolutionary Computation 8, no. 4 (December 2000): 419–42. http://dx.doi.org/10.1162/106365600568248.

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We evaluate whether John Holland's Echo model exemplifies his theory of complex adaptive systems. After reviewing Holland's theory of complex adaptive systems and describing his Echo model, we describe and explain the characteristic evolutionary behavior observed in a series of Echo model runs. We conclude that Echo lacks the diversity of hierarchically organized aggregates that typify complex adaptive systems, and we explore possible explanations for this failure.
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Matos, Francisco Gomes de. "Language as a complex adaptive system." DELTA: Documentação de Estudos em Lingüística Teórica e Aplicada 26, no. 2 (2010): 425–28. http://dx.doi.org/10.1590/s0102-44502010000200010.

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Alberto, Díaz, Castilla Alberto, and Lebersztein Gabriel. "The Hospital: A Complex Adaptive System." Asian Journal of Medicine and Health 5, no. 1 (January 10, 2017): 1–5. http://dx.doi.org/10.9734/ajmah/2017/34421.

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Lierman, Steven. "Law as a Complex Adaptive System." Maastricht Journal of European and Comparative Law 21, no. 4 (December 2014): 611–29. http://dx.doi.org/10.1177/1023263x1402100403.

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Bobo, Lawrence D. "RACE AS A COMPLEX ADAPTIVE SYSTEM." Du Bois Review: Social Science Research on Race 15, no. 02 (2018): 211–15. http://dx.doi.org/10.1017/s1742058x19000043.

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Armstrong, Gordon. "Theatre as a Complex Adaptive System." New Theatre Quarterly 13, no. 51 (August 1997): 277–88. http://dx.doi.org/10.1017/s0266464x00011271.

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The functioning of human consciousness in interpreting and staging a theatrical performance is, as Gordon Armstrong argues in this article, among the most highly selective and adaptive operations known to physical science. According to this view, the theatre, as a substrate of consciousness, was part of the package that defined modern man as a reflective species: whereas for the first four million years of human existence man was silent about a probable inner life, the dawn of empathy some 200,000 years ago saw a neural explosion – the enlargement of the angular gyrus in the left hemisphere of the brain, unlocking a new kind of reflective consciousness. In isolation, this aberrant neurological connection proved so advantageous for hunting and for communication that members of a tribe who possessed this aberration prospered: and adaptation to the ice ages that began 200,000 years ago was a motivating factor in stimulating the emergence of what we can recognize as art. Gordon Armstrong is immediate past Secretary of the American Society for Theatre Research, and Review Editor for Theatre Research International. He has taught at UCLA, SUNY Stony Brook, and the University of Rhode Island, and has designed and directed productions in San Francisco, Los Angeles, and New York. His full-length works include the revised Golden Ages of the Theatre and Samuel Beckett, W.B. Yeats, and Jack Yeats: Images and Words.
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Schwab, E. D., and K. J. Pienta. "Cancer as a complex adaptive system." Medical Hypotheses 47, no. 3 (September 1996): 235–41. http://dx.doi.org/10.1016/s0306-9877(96)90086-9.

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Haris, Khaled, and Cihan H. Dagli. "Adaptive Reconfiguration of Complex System Architecture." Procedia Computer Science 6 (2011): 147–52. http://dx.doi.org/10.1016/j.procs.2011.08.029.

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Lenton, Timothy M., and Marcel van Oijen. "Gaia as a complex adaptive system." Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 357, no. 1421 (May 29, 2002): 683–95. http://dx.doi.org/10.1098/rstb.2001.1014.

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We define the Gaia system of life and its environment on Earth, review the status of the Gaia theory, introduce potentially relevant concepts from complexity theory, then try to apply them to Gaia. We consider whether Gaia is a complex adaptive system (CAS) in terms of its behaviour and suggest that the system is self–organizing but does not reside in a critical state. Gaia has supported abundant life for most of the last 3.8 Gyr. Large perturbations have occasionally suppressed life but the system has always recovered without losing the capacity for large–scale free energy capture and recycling of essential elements. To illustrate how complexity theory can help us understand the emergence of planetary–scale order, we present a simple cellular automata (CA) model of the imaginary planet Daisyworld. This exhibits emergent self–regulation as a consequence of feedback coupling between life and its environment. Local spatial interaction, which was absent from the original model, can destabilize the system by generating bifurcation regimes. Variation and natural selection tend to remove this instability. With mutation in the model system, it exhibits self–organizing adaptive behaviour in its response to forcing. We close by suggesting how artificial life (‘Alife’) techniques may enable more comprehensive feasibility tests of Gaia.
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Dissertations / Theses on the topic "Complex and adaptive system"

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Engler, Joseph John. "Innovation as a complex adaptive system." Thesis, University of Iowa, 2009. https://ir.uiowa.edu/etd/233.

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Innovation has long been considered crucial for companies to gain a competitive edge in the global marketplace. Unfortunately, a solid understanding of the system of innovation does not exist. The literature lacks formal definitions and methodologies for the system of innovation. Many surrogates for innovation metrics have been posited in past research but none have solidified the overall concept of an innovation system or science. It has been speculated that innovation as a system is complex. Additionally, some researchers have suggested that this innovation system is adaptive. In these instances, of the literature, surrogates were again utilized in place of solid modeling and hypothesis that is benchmarked against real world case studies. Surrogates, such as patent citation, do serve a useful purpose to assist in the understanding of the historic nature of the innovation system but they fall short of defining the system completely. This paper seeks to aid in the solidification of a hypothesis of the system of innovation as a complex adaptive system. Initial consideration is directed towards the historic interactions that have taken place in the system of innovation. These interactions are viewed through the surrogate of patent citation as there is little other record of innovation. The novelty of this paper is that patent citations form not the core but rather a starting point for the definition of innovation as a complex adaptive system. Various models are built using techniques of cellular automata as well as agent-based modeling to assist in the understanding of the principles at work in the innovation system. These models present startling evidence that there exists an upper bound on the number of interactions any one invention should utilize in its course towards being deemed an innovation. Additionally, the models describe the benefits of partnership between innovating entities in a rapidly changing marketplace such as the current technological markets. This paper asserts specific conclusions, from the models, that assist in understanding that the system of innovation is truly a complex adaptive system. The models are further supported through real world examples.
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Lear, Matthew R. "Forecasting hurricane tracks using a complex adaptive system." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2005. http://library.nps.navy.mil/uhtbin/hyperion/05Jun%5FLear%5FMetoc.pdf.

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Lear, Matthew R. "A complex adaptive system approach to forecasting hurricane tracks." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2005. http://library.nps.navy.mil/uhtbin/hyperion/05Jun%5FLear%5FCS.pdf.

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Wellbrink, Joerg C. G. "Modeling reduced human performance as a complex adaptive system." Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2003. http://library.nps.navy.mil/uhtbin/hyperion-image/03sep%5FWellbrink%5FPhD.pdf.

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Nisula, Jari M. "A risk management framework for a complex adaptive transport system." Thesis, Toulouse 3, 2018. http://www.theses.fr/2018TOU30041.

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La science a connu des avancées significatives en matière de gestion du risque au cours de la dernière décennie. Toutefois, les pratiques actuelles de gestion du risque dans le domaine industriel n'ont pas tiré tout le profit de ces développements. Le sujet de recherche de cette thèse peut être formulé ainsi : comment bâtir un cadre de gestion du risque afin de gérer les risques dans le transport, en adoptant les perspectives modernes du risque et les dernières connaissances de sécurité, tout en considérant le système de transport comme un système adaptatif complexe ? Ceci, à travers la perspective d'une agence nationale de la sécurité des transports, dont la responsabilité est la supervision de la sécurité de plusieurs modes de transport, incluant l'aérien, le maritime, le ferroviaire et le routier. La connaissance scientifique actuelle est passée en revue pour les sujets de risques et d'appréciation du risque, de sécurité et de gestion de la sécurité ainsi que les systèmes adaptatifs complexes. L'approche moderne du risque implique reconnaitre l'importance de l'incertitude et la solidité des connaissances dans l'analyse du risque ainsi que le rôle des imprévus. Le système de transport est identifié comme un système adaptatif complexe. De tels systèmes se caractérisent par un large volume d'interactions, de nombreuses boucles de rétroaction, des phénomènes non-linéaires, l'émergence, l'imprévisibilité et la contre-intuitivité. Sont étudiées les façons recommandées d'interagir avec les systèmes complexes afin de tenter de parvenir à un changement positif. Les concepts relatifs à la gestion de la sécurité sont également présentés et notamment le concept de résilience qui peut être interprété soit comme une élégante extensibilité des équipes ou des organisations, soit comme une adaptabilité continue. Les cadres existants de management du risque sont revus à la fois dans l'industrie et dans la littérature scientifique ainsi que la norme internationale ISO 31000. Basé sur l'état de l'art, un ensemble de critères pour un processus moderne de management du risque est développé. Le cadre proposé de gestion du risque dans le transport comprend des perspectives modernes du risque et considère le système de transport comme un système adaptatif complexe. Il permet de présenter les risques des différents modes de transport dans une visualisation globale de risque et de l'utiliser en tant que support pour prise de décision afin d'optimiser l'impact sur la sécurité avec les ressources qui sont toujours limitées. L'impact est encore renforcé par les moyens d'intervention tels que les stratégies adaptives et l'expérimentation, qui sont bien adaptés aux systèmes complexes. Elle est validée selon les critères élaborés et par comparaison avec les cadres existants. Le cadre proposé de gestion du risque ainsi que la thèse sont tous deux structurés d'après la norme ISO 31000. Enfin une étude de cas présente la mise en œuvre actuelle de cette nouvelle approche à l'Agence Nationale Finlandaise de la Sécurité des Transports
Over the last ten-fifteen years, science has made significant advances in fields relevant for risk management. However, current risk management practices in industry have not yet benefitted from these developments. The research question addressed in this dissertation is: What kind of risk management framework should be used for managing transport risks when the modern risk perspectives and the latest understanding of safety are embraced, and the transport system is considered a complex adaptive system? The focus of this research is on transport risks, taking the perspective of a national transport safety agency, tasked with overseeing safety across several modes of transport, including aviation, maritime, railway and road safety. The scientific literature on risk and risk assessment, safety and safety management, as well as complex adaptive systems are reviewed. The research illustrates that a modern risk perspective recognizes the importance of uncertainty and strength of knowledge in risk analysis, as well as the role of surprises. The transport system is identified as a complex adaptive system, characterized by a high number of interactions, emergence, multiple feedback loops, nonlinear phenomena, unpredictability and counter-intuitiveness. The recommended ways to interact with such complex systems and to try to achieve positive change are explained. Concepts related to safety management are also investigated, especially the concept of resilience, which is interpreted as graceful extensibility of teams or organizations, or as sustained adaptability. Evidence of existing risk management frameworks in both the industry and scientific literature is outlined and reference is made to the international ISO 31000 standard for risk management. Based on the literature review, a set of criteria for a modern risk management process is developed. A risk management framework for managing transport risks which embraces modern risk perspectives and accounts for the transport system as a complex adaptive system is proposed. It enables risks in all transport modes to be presented in a single risk picture and supports decision-making to maximize the safety impact achievable with limited resources. The impact is further enhanced by intervention strategies such as adaptive policies and experimentation, which are well-suited to complex systems. The framework is validated against the criteria developed, and by comparison to existing methods. A case study presents the on-going implementation of the developed risk management framework at the Finnish Transport Safety Agency. Both the proposed risk management framework and the dissertation are structured according to the ISO 31000 framework
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Bondorowicz, Stefan. "Adaptive control of complex dynamic systems." Thesis, University of Oxford, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.302787.

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Mukri, Farha. "Business-IT Traceability for Complex System Improvement." The Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=osu1250608349.

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Sullivan, John P. "Emergent Learning: Three Learning Communities as Complex Adaptive Systems." Thesis, Boston College, 2009. http://hdl.handle.net/2345/663.

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Thesis advisor: Patrick J. McQuillan
In the 2007-2008 school year, the author conducted a collaborative case study (Stake, 2000) with the goal of discovering and describing "emergent learning" in three high school classrooms. Emergent learning, defined as the acquisition of new knowledge by an entire group when no individual member of the group possessed it before, is implied by the work of many theorists working on an educational analog of a natural phenomenon called a complex adaptive system. Complex adaptive systems are well networked collectives of agents that are non-linear, bounded and synergistic. The author theorized that classes that maximized the features of complex adaptive systems could produce emergent learning (a form of synergy), and that there was a continuum of this complexity, producing a related continuum of emergence. After observing a co-curricular jazz group, an English class, and a geometry class for most of one academic year, collecting artifacts and interviewing three students and a teacher from each class, the author determined that there was indeed a continuum of complexity. He found that the actively complex nature of the Jazz Rock Ensemble produced an environment where emergence was the norm, with the ensemble producing works of music, new to the world, with each performance. The English section harnessed the chaotic tendencies of students to optimize cognitive dissonance and frequently produce emergent learning, while the mathematics section approached the learning process in a way that was too rigidly linear to allow detectable emergence to occur
Thesis (PhD) — Boston College, 2009
Submitted to: Boston College. Lynch School of Education
Discipline: Teacher Education, Special Education, Curriculum and Instruction
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Mains, Steven. "Optimizing combat capabilities by modeling combat as a complex adaptive system." W&M ScholarWorks, 2004. https://scholarworks.wm.edu/etd/1539623454.

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Procuring combat systems in the Department of Defense is a balancing act where many variables, only some under control of the department, shift simultaneously. Technology changes non-linearly, providing new opportunities and new challenges to the existing and potential force. Money available changes year over year to fit into the overall US Government budget. Numbers of employees change through political demands rather than by cost-effectiveness considerations. The intent is to provide the best mix of equipment to field the best force against an expected enemy while maintaining adequate capability against the unexpected. Confounding this desire is the inability of current simulations to dynamically model changing capabilities and the very large universe of potential combinations of equipment and tactics.;The problem can be characterized as a stochastic, mixed-integer, non-linear optimization problem. This dissertation proposes to combine an agent-based model developed to test solutions that constitute both equipment capabilities and tactics with a co-evolutionary genetic algorithm to search this hyper-dimensional solution space. In the process, the dissertation develops the theoretical underpinning for using agent-based simulations to model combat. It also provides the theoretical basis for improvement of search effectiveness by co-evolving multiple systems simultaneously, which increases exploitation of good schemata and widens exploration of new schemata. Further, it demonstrates the effectiveness of using agent-based models and co-evolution in this application confirming the theoretical results.;An open research issue is the value of increased information in a system. This dissertation uses the combination of an agent-based model with a co-evolutionary genetic algorithm to explore the value added by increasing information in a system. The result was an increased number of fit solutions, rather than an increase in the fitness of the best solutions. Formerly unfit solutions were improved by increasing the information available making them competitive with the most fit solutions whereas already fit solutions were not improved.
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Shenoy, Rajiv. "Overset adaptive strategies for complex rotating systems." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/51796.

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The resolution of the complex physics of rotating configurations is critical for any engineering analysis that requires multiple frames of reference. Two well-known applications are in the rotorcraft and wind energy industries. Rotor wake impingement from rotor-fuselage and wind turbine-tower interactions impact structural and acoustic characteristics. Additionally, parasite drag resulting from rotorcraft hubs may result in severe limitations on forward flight vehicle performance. Complex turbulent wakes from rotors and hubs impinging on downstream empennage can create adverse aeroelastic behavior and can affect handling qualities. Numerical simulations of these flows require state-of-the-art Navier Stokes methods using dynamic overset grids. However, many current methods typically used in industry result in wakes that dissipate essential features. In order to address these concerns, two advancements are introduced in this thesis. Feature-based grid adaptation on dynamic overset grids has been developed and demonstrated with an unstructured Navier Stokes solver. The unique feature of the adaptation technique is that it is applied globally on the overset grid system except within the boundary layer. In concert with grid adaptation, an efficient parallelized search algorithm for solution interpolation over massively distributed systems has been created. This results in cost-effective interpolation that retains the numerical order of accuracy and has been verified in both space and time. The improvements have been demonstrated for rotor-fuselage interaction and a generic rotating hub. Detailed analysis of convergence of the methodology and sensitivity of the results to relevant parameters have also been included.
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Books on the topic "Complex and adaptive system"

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Carmichael, Ted, Andrew J. Collins, and Mirsad Hadžikadić, eds. Complex Adaptive Systems. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-20309-2.

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C, Ellis Nick, Larsen-Freeman Diane, and Research Club in Language Learning (Ann Arbor, Mich.), eds. Language as a complex adaptive system. Malden, MA: Blackwell Pub., 2009.

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C, Ellis Nick, Larsen-Freeman Diane, and Research Club in Language Learning (Ann Arbor, Mich.), eds. Language as a complex adaptive system. Malden, MA: Blackwell Pub., 2009.

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C, Ellis Nick, Larsen-Freeman Diane, and Research Club in Language Learning (Ann Arbor, Mich.), eds. Language as a complex adaptive system. Malden, MA: Blackwell Pub., 2009.

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Ellis, Nick C. Language as a complex adaptive system. Edited by Research Club in Language Learning (Ann Arbor, Mich.). Chichester, West Sussex, U.K: Wiley-Blackwell, 2009.

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Ang, Yang, and Shan Yin, eds. Intelligent complex adaptive systems. Hershey: IGI Pub., 2008.

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Ang, Yang, and Shan Yin, eds. Applications of complex adaptive systems. Hershey, PA: IGI Pub., 2008.

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Baicchi, Annalisa. Construction Learning as a Complex Adaptive System. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-18269-8.

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J, Stonier Russel, and Xing Huo-yu, eds. Complex systems: Mechanism of adaptation. Amsterdam: IOS Press, 1994.

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Gros, Claudius. Complex and Adaptive Dynamical Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36586-7.

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Book chapters on the topic "Complex and adaptive system"

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Shultz, Thomas R., Scott E. Fahlman, Susan Craw, Periklis Andritsos, Panayiotis Tsaparas, Ricardo Silva, Chris Drummond, et al. "Complex Adaptive System." In Encyclopedia of Machine Learning, 194. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-0-387-30164-8_147.

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Fidanboy, Mahsa. "System." In Organizations and Complex Adaptive Systems, 1–17. New York: Routledge, 2022. http://dx.doi.org/10.4324/9781003182764-1.

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Sturmberg, Joachim P. "Visualisation of Complex Adaptive Systems." In Health System Redesign, 45–51. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64605-3_3.

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Gross, Thilo, and Hiroki Sayama. "Adaptive Networks." In Understanding Complex Systems, 1–8. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01284-6_1.

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Niazi, Muaz A., and Amir Hussain. "Complex Adaptive Systems." In Cognitive Agent-based Computing-I, 21–32. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-3852-2_3.

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da Silva Vieira, Ricardo. "Complex Adaptive Systems." In Industry, Innovation and Infrastructure, 1–11. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-71059-4_11-1.

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Dekkers, Rob. "Complex Adaptive Systems." In Applied Systems Theory, 169–90. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10846-9_8.

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Haefner, James W. "Complex Adaptive Systems." In Modeling Biological Systems, 424–37. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4615-4119-6_20.

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Whalen, Thomas B. "Complex adaptive systems." In Complexity, Society and Social Transactions, 61–67. Abingdon, Oxon ; NewYork, NY : Routledge, 2018. | Series: Routledge studies in social and political thought: Routledge, 2017. http://dx.doi.org/10.4324/9781315179919-9.

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Iba, Hitoshi. "Complex Adaptive Systems." In AI and SWARM, 137–59. First edition. | Boca Raton, FL : CRC Press/Taylor & Francis Group, 2019.: CRC Press, 2019. http://dx.doi.org/10.1201/9780429027598-5.

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Conference papers on the topic "Complex and adaptive system"

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Voss, Mark S., and Xin Feng. "Emergent system identification using particle swarm optimization." In Complex Adaptive Structures, edited by William B. Spillman, Jr. SPIE, 2001. http://dx.doi.org/10.1117/12.446767.

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Maleki-dizaji, Saeedeh, H. O. Nyongesa, and J. Siddiqqi. "Adaptive multi-agent system for information retrieval." In Complex Adaptive Structures, edited by William B. Spillman, Jr. SPIE, 2001. http://dx.doi.org/10.1117/12.446766.

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Crisman, Mark V. "Integration of the immune system: a complex adaptive supersystem." In Complex Adaptive Structures, edited by William B. Spillman, Jr. SPIE, 2001. http://dx.doi.org/10.1117/12.446761.

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Meissner, Ken E. "Adaptive optical system for improved activation of PDT photosensitizers." In Complex Adaptive Structures. SPIE, 2001. http://dx.doi.org/10.1117/12.446776.

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Varadan, Vijay K. "MEMS- and NEMS-based complex adaptive smart devices and systems." In Complex Adaptive Structures, edited by William B. Spillman, Jr. SPIE, 2001. http://dx.doi.org/10.1117/12.446770.

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White, B. E. "Complex Adaptive Systems Engineering (CASE)." In 2009 3rd Annual IEEE Systems Conference. IEEE, 2009. http://dx.doi.org/10.1109/systems.2009.4815774.

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Arshad, Saba, Hafsa Maryam, Humera Yasmeen, and Munam Ali Shah. "Complex Adaptive Systems." In the 2nd International Conference. New York, New York, USA: ACM Press, 2018. http://dx.doi.org/10.1145/3206098.3206120.

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Chen, Jiang, Liu Ming, Li Xiong, Fu Jia, and Dong Fei. "Modeling for complex adaptive system organization." In 2011 International Conference on Consumer Electronics, Communications and Networks (CECNet). IEEE, 2011. http://dx.doi.org/10.1109/cecnet.2011.5768360.

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Assoudi, Hicham, and Hakim Lounis. "Schema Matching as complex adaptive system." In 2015 10th International Conference on Intelligent Systems: Theories and Applications (SITA). IEEE, 2015. http://dx.doi.org/10.1109/sita.2015.7358442.

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Vakili, Golnaz, and Siavash Khorsandi. "Engineering a peer to peer architecture: A complex adaptive system approach." In 2010 4th Annual IEEE Systems Conference. IEEE, 2010. http://dx.doi.org/10.1109/systems.2010.5482487.

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Reports on the topic "Complex and adaptive system"

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Petrie, Samuel, and Paul A. Peters. Implementation considerations in a Complex Adaptive System. Carleton University, September 2018. http://dx.doi.org/10.22215/sdhlab/2018.9.

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2

Linebarger, John Michael, S. Louise Maffitt, Robert John, Jr Glass, Walter Eugene Beyeler, and Arlo Leroy Ames. Complex Adaptive System of Systems (CASoS) Engineering Applications. Version 1.0. Office of Scientific and Technical Information (OSTI), October 2011. http://dx.doi.org/10.2172/1038214.

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3

Moore, Thomas W., Tu-Thach Quach, Richard Joseph Detry, Stephen Hamilton Conrad, Andjelka Kelic, Shirley J. Starks, Walter Eugene Beyeler, et al. Phoenix : Complex Adaptive System of Systems (CASoS) engineering version 1.0. Office of Scientific and Technical Information (OSTI), August 2011. http://dx.doi.org/10.2172/1038215.

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4

Lichtblau, Dale E., Brian A. Haugh, Gregory N. Larsen, and Terry Mayfield. Analyzing Adversaries as Complex Adaptive Systems. Fort Belvoir, VA: Defense Technical Information Center, October 2006. http://dx.doi.org/10.21236/ada464073.

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5

Chassin, David P., Joel M. Malard, Christian Posse, Asim Gangopadhyaya, Ning Lu, Srinivas Katipamula, and J. V. Mallow. Modeling Power Systems as Complex Adaptive Systems. Office of Scientific and Technical Information (OSTI), December 2004. http://dx.doi.org/10.2172/877087.

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6

Tolley, George S. HYDROGEN PRODUCTION AND DELIVERY INFRASTRUCTURE AS A COMPLEX ADAPTIVE SYSTEM. Office of Scientific and Technical Information (OSTI), June 2010. http://dx.doi.org/10.2172/1056227.

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7

Detry, Richard Joseph, John Michael Linebarger, Patrick D. Finley, S. Louise Maffitt, Robert John, Jr Glass, Walter Eugene Beyeler, and Arlo Leroy Ames. Complex Adaptive Systems of Systems (CASOS) engineering environment. Office of Scientific and Technical Information (OSTI), February 2012. http://dx.doi.org/10.2172/1038222.

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8

Busch, Timothy E., and Dawn A. Trevisani. Modeling of Complex Adaptive Systems in Air Operations. Fort Belvoir, VA: Defense Technical Information Center, September 2006. http://dx.doi.org/10.21236/ada457738.

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9

HARRIS, DAVID L. Echo Implemented: A Model for Complex Adaptive Systems Computer Experimentation. Office of Scientific and Technical Information (OSTI), July 2001. http://dx.doi.org/10.2172/786628.

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10

Colvin, Nathan M. A Complex Adaptive Systems Approach to the Future Operational Environment. Fort Belvoir, VA: Defense Technical Information Center, May 2014. http://dx.doi.org/10.21236/ada611766.

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