Littérature scientifique sur le sujet « Complex systems learning »
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Articles de revues sur le sujet "Complex systems learning"
ELMS, DAVID G. « LEARNING ABOUT COMPLEX SYSTEMS ». Civil Engineering Systems 9, no 3 (octobre 1992) : 265–72. http://dx.doi.org/10.1080/02630259208970653.
Texte intégralWong, K. Y. Michael, S. Li et Y. W. Tong. « Complex dynamics in learning systems ». Physica A : Statistical Mechanics and its Applications 288, no 1-4 (décembre 2000) : 397–401. http://dx.doi.org/10.1016/s0378-4371(00)00436-2.
Texte intégralSterman, John D. « Learning In and About Complex Systems ». Reflections : The SoL Journal 1, no 3 (1 mars 2000) : 24–51. http://dx.doi.org/10.1162/152417300570050.
Texte intégralSterman, John D. « Learning in and about complex systems ». System Dynamics Review 10, no 2-3 (1994) : 291–330. http://dx.doi.org/10.1002/sdr.4260100214.
Texte intégralLawson, Hal A., Dawn Anderson-Butcher, Nancy Petersen et Carenlee Barkdull. « Design Teams as Learning Systems for Complex Systems Change ». Journal of Human Behavior in the Social Environment 7, no 1-2 (janvier 2003) : 159–79. http://dx.doi.org/10.1300/j137v07n01_11.
Texte intégralHerrington, Jessica, Ted Maddess, Dominique Coy, Corinne Carle, Faran Sabeti et Marconi Barbosa. « Learning Complex Texture Discrimination ». Journal of Vision 18, no 10 (1 septembre 2018) : 260. http://dx.doi.org/10.1167/18.10.260.
Texte intégralKim, Jaehun. « Increasing trust in complex machine learning systems ». ACM SIGIR Forum 55, no 1 (juin 2021) : 1–3. http://dx.doi.org/10.1145/3476415.3476435.
Texte intégralKempe, Vera, et Patricia J. Brooks. « Second Language Learning of Complex Inflectional Systems ». Language Learning 58, no 4 (décembre 2008) : 703–46. http://dx.doi.org/10.1111/j.1467-9922.2008.00477.x.
Texte intégralAllen, Peter M., et Mark Strathern. « Evolution, Emergence, and Learning in Complex Systems ». Emergence 5, no 4 (décembre 2003) : 8–33. http://dx.doi.org/10.1207/s15327000em0504_4.
Texte intégralHuang, Xueqin, Xianqiang Zhu, Xiang Xu, Qianzhen Zhang et Ailin Liang. « Parallel Learning of Dynamics in Complex Systems ». Systems 10, no 6 (15 décembre 2022) : 259. http://dx.doi.org/10.3390/systems10060259.
Texte intégralThèses sur le sujet "Complex systems learning"
Sullivan, John P. « Emergent Learning : Three Learning Communities as Complex Adaptive Systems ». Thesis, Boston College, 2009. http://hdl.handle.net/2345/663.
Texte intégralIn 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
Attebo, Edvin. « Safe learning and control in complex systems ». Thesis, Umeå universitet, Institutionen för fysik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-178164.
Texte intégralBondorowicz, Stefan. « Adaptive control of complex dynamic systems ». Thesis, University of Oxford, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.302787.
Texte intégralEagle, Nathan Norfleet. « Machine perception and learning of complex social systems ». Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/32498.
Texte intégralIncludes bibliographical references (p. 125-136).
The study of complex social systems has traditionally been an arduous process, involving extensive surveys, interviews, ethnographic studies, or analysis of online behavior. Today, however, it is possible to use the unprecedented amount of information generated by pervasive mobile phones to provide insights into the dynamics of both individual and group behavior. Information such as continuous proximity, location, communication and activity data, has been gathered from the phones of 100 human subjects at MIT. Systematic measurements from these 100 people over the course of eight months has generated one of the largest datasets of continuous human behavior ever collected, representing over 300,000 hours of daily activity. In this thesis we describe how this data can be used to uncover regular rules and structure in behavior of both individuals and organizations, infer relationships between subjects, verify self- report survey data, and study social network dynamics. By combining theoretical models with rich and systematic measurements, we show it is possible to gain insight into the underlying behavior of complex social systems.
by Nathan Norfleet Eagle.
Ph.D.
Al-Jubouri, Bassma. « Multi-criteria optimisation for complex learning prediction systems ». Thesis, Bournemouth University, 2018. http://eprints.bournemouth.ac.uk/30857/.
Texte intégralTong, Xiao Thomas. « Statistical Learning of Some Complex Systems : From Dynamic Systems to Market Microstructure ». Thesis, Harvard University, 2013. http://dissertations.umi.com/gsas.harvard:10917.
Texte intégralStatistics
Passey, Jr David Joseph. « Growing Complex Networks for Better Learning of Chaotic Dynamical Systems ». BYU ScholarsArchive, 2020. https://scholarsarchive.byu.edu/etd/8146.
Texte intégralCERBONI, BAIARDI LORENZO. « Adaptive models of learning in complex physical and social systems ». Doctoral thesis, Urbino, 2016. http://hdl.handle.net/11576/2630552.
Texte intégralTopcu, Taylan Gunes. « Management of Complex Sociotechnical Systems ». Diss., Virginia Tech, 2020. http://hdl.handle.net/10919/97844.
Texte intégralDoctor of Philosophy
A system is an integrated set of elements that achieve a purpose or goal. An autonomous system (ADS) is an engineered element that often substitutes for a human decision-maker, such as in the case of an autonomous vehicle. Sociotechnical systems (STSs) are systems that involve the collaboration of a human decision-maker with an ADS to fulfill their objectives. Historically, STSs have been used primarily for handling safety critical tasks, such as management of nuclear power plants. By design, STSs rely heavily on a collaboration between humans and ADS decision-makers. Therefore, the overall characteristics of a STS, such as system safety, performance, or reliability; is fully dependent on human decisions. The problem with that is that people are independent entities, who can be influenced by operational conditions. Unlike their engineered counterparts, people can be cognitively challenged, tired, or distracted, and consequently make mistakes. The current dependency on human decisions, incentivize business owners and engineers alike to increase the level of automation in engineered systems. This allows them to reduce operational costs, increase performance, and minimize human errors. However, the recent commercial aircraft accidents (e.g., Boeing 737-MAX) have indicated that increasing the level of automation is not always the best strategy. Given that increasing technological capabilities will spread the adoption of STSs, vast majority of existing jobs will either be fully replaced by an ADS or will change from a manual set-up into a STS. Therefore, we need a better understanding of the relationships between social (human) and engineered elements. This dissertation, brings together management science with systems thinking to investigate the dependencies between people and the autonomous systems they collaborate within complex socio-technical enterprises. The dissertation is organized in three mutually exclusive essays, each investigating a distinct facet of STSs: safe management, collaboration, and efficiency measurement. The first essay investigates the amount of work handled by safety-critical decision makers in STSs. Primary contribution of this study is to use an analytic method to quantify the amount of work a person could safely handle within a STSs. This method also allows to capture the aggregate impact of the social and technical factors that originate from operational conditions on workload. The second essay studies how teams of humans and their autonomous partners share work, given their preferences and operational conditions. This study presents a novel integration of machine learning algorithms to understand operational influences that propel a human-decision maker to handle the work manually or delegate it to ADSs. The results demonstrate that autonomous units successfully handle simple operational conditions. More complex conditions require both workers and their autonomous counterparts to collaborate towards common objectives. The third essay explores the complementary and contrasting roles of data-driven analytical management approaches that deal with the operational factors and investigates their sensitivity to sample size. The results are organized based on their fundamental assumptions, limitations, mathematical structure, sensitivity to sample size, and their practical usefulness. To summarize, this dissertation provides an interdisciplinary and pragmatic research approach that benefits from the strengths of both theoretical and data-driven empirical approaches. Broader impacts of this dissertation are disseminated among the literatures of systems engineering, operations research, management science, and mechanical design.
Urwin, Gerry. « Learning from complex information systems implementation : case studies in ERP projects ». Thesis, Henley Business School, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.268860.
Texte intégralLivres sur le sujet "Complex systems learning"
Grigoʹevich, Ivakhnenko Alekseĭ, dir. Inductive learning algorithms for complex systems modeling. Boca Raton : CRC Press, 1994.
Trouver le texte intégral1948-, Prete Frederick R., dir. Complex worlds from simpler nervous systems. Cambridge, Mass : MIT Press, 2004.
Trouver le texte intégralRuan, Da. Computational intelligence in complex decision systems. Paris : Atlantis Press, 2010.
Trouver le texte intégralF, Chipman Susan, et Meyrowitz Alan L, dir. Foundations of knowledge acquisition : Cognitive models of complex learning. Boston : Kluwer Academic, 1993.
Trouver le texte intégral1967-, Caballe Santi, dir. Architectures for distributed and complex M-learning systems : Applying intelligent technologies. Hershey, PA : Information Science Reference, 2010.
Trouver le texte intégral1951-, Kirschner Paul Arthur, dir. Ten steps to complex learning : A systematic approach to four-component instructional design. Mahwah, N.J : Lawrence Erlbaum Associates, 2007.
Trouver le texte intégral1951-, Kirschner Paul Arthur, dir. Ten steps to complex learning : A systematic approach to four-component instructional design. 2e éd. New York : Routledge, 2012.
Trouver le texte intégralTraining complex cognitive skills : A Four-Component Instructional Design model for technical training. Englewood Cliffs, N.J : Educational Technology Publications, 1997.
Trouver le texte intégralSocietal Learning and Change : How Governments, Business and Civil Society are Creating Solutions to Complex Multi-Stakeholder Problems. London : Taylor and Francis, 2017.
Trouver le texte intégralSocietal learning and change : How governments, business and civil society are creating solutions to complex multi-stakeholder problems. Sheffield : Greenleaf Pub., 2005.
Trouver le texte intégralChapitres de livres sur le sujet "Complex systems learning"
Macy, Michael W., Stephen Benard et Andreas Flache. « Learning ». Dans Understanding Complex Systems, 431–53. Berlin, Heidelberg : Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-540-93813-2_17.
Texte intégralMacy, Michael W., Steve Benard et Andreas Flache. « Learning ». Dans Understanding Complex Systems, 501–23. Cham : Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-66948-9_20.
Texte intégralMoser, Hubert Anton. « Systems Engineering and Learning ». Dans Understanding Complex Systems, 11–57. Cham : Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-03895-7_2.
Texte intégralHelbing, Dirk. « Learning of Coordinated Behavior ». Dans Understanding Complex Systems, 211–37. Berlin, Heidelberg : Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-24004-1_12.
Texte intégralNguyen, Dai Hai, Canh Hao Nguyen et Hiroshi Mamitsuka. « Machine Learning for Metabolic Identification ». Dans Creative Complex Systems, 329–50. Singapore : Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-4457-3_20.
Texte intégralZanone, Pier-Giorgio, et Viviane Kostrubiec. « Searching for (Dynamic) Principles of Learning ». Dans Understanding Complex Systems, 57–89. Berlin, Heidelberg : Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-39676-5_4.
Texte intégralTonsberg, Terje Andreas, et Jeffrey Shawn Henderson. « Some A Priori Aspects of Learning ». Dans Understanding Complex Systems, 153–54. Cham : Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-40445-5_19.
Texte intégralRogers, Eric, Chris T. Freeman, Ann-Marie Hughes, Jane H. Burridge, Katie L. Meadmore et Tim Exell. « Iterative Learning Control as an Enabler for Robotic-Assisted Upper Limb Stroke Rehabilitation ». Dans Complex Systems, 157–87. Cham : Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-28860-4_8.
Texte intégralLee, Timothy D. « Intention in Bimanual Coordination Performance and Learning ». Dans Understanding Complex Systems, 41–56. Berlin, Heidelberg : Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-39676-5_3.
Texte intégralDimirovski, G. M., A. Dourado, E. Ikonen, U. Kortela, J. Pico, B. Ribeiro, M. J. Stankovski et E. Tulunay. « Learning Control of Thermal Systems ». Dans Control of Complex Systems, 317–37. London : Springer London, 2001. http://dx.doi.org/10.1007/978-1-4471-0349-3_14.
Texte intégralActes de conférences sur le sujet "Complex systems learning"
Burdet, G. « Geometrical methods in learning theory ». Dans Disordered and complex systems. AIP, 2001. http://dx.doi.org/10.1063/1.1358171.
Texte intégralBuhot, Arnaud. « Storage capacity of the Tilinglike Learning Algorithm ». Dans Disordered and complex systems. AIP, 2001. http://dx.doi.org/10.1063/1.1358157.
Texte intégralAxtell, Travis, Lucas A. Overbey et Lisa Woerner. « Machine learning in complex systems ». Dans Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IX, sous la direction de Tien Pham, Michael A. Kolodny et Dietrich M. Wiegmann. SPIE, 2018. http://dx.doi.org/10.1117/12.2309547.
Texte intégralHamagami, Tomoki, Takashi Shibuya et Shingo Shimada. « Complex-Valued Reinforcement Learning ». Dans 2006 IEEE International Conference on Systems, Man and Cybernetics. IEEE, 2006. http://dx.doi.org/10.1109/icsmc.2006.384789.
Texte intégralLorscheid, Iris. « Learning Agents for Human Complex Systems ». Dans 2014 IEEE 38th International Computer Software and Applications Conference Workshops (COMPSACW). IEEE, 2014. http://dx.doi.org/10.1109/compsacw.2014.73.
Texte intégralZhang, Song-bao, Jin-cai Huang, Wei-ming Zhang et Zhong Liu. « Research on Parallel Decision Analyzing for Complex System of Systems ». Dans 2006 International Conference on Machine Learning and Cybernetics. IEEE, 2006. http://dx.doi.org/10.1109/icmlc.2006.258986.
Texte intégralRajeswaran, Aravind, Vikash Kumar, Abhishek Gupta, Giulia Vezzani, John Schulman, Emanuel Todorov et Sergey Levine. « Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations ». Dans Robotics : Science and Systems 2018. Robotics : Science and Systems Foundation, 2018. http://dx.doi.org/10.15607/rss.2018.xiv.049.
Texte intégralOuali-Alami, Chaimae, Abdelali El Bdouri, Nisrine Elmarzouki, Ayoub Korchi et Younes Lakhrissi. « Approaches to Design Complex Software Systems ». Dans INTERNATIONAL CONFERENCE ON BIG DATA, MODELLING AND MACHINE LEARNING (BML'21). SCITEPRESS - Science and Technology Publications, 2021. http://dx.doi.org/10.5220/0010740200003101.
Texte intégralJohnson, Michael, et Betsy DiSalvo. « Learning about Complex Adaptive Systems in Makerspaces ». Dans SIGCSE 2022 : The 53rd ACM Technical Symposium on Computer Science Education. New York, NY, USA : ACM, 2022. http://dx.doi.org/10.1145/3478432.3499243.
Texte intégralDobre, Mihai S., et Alex Lascarides. « Exploiting action categories in learning complex games ». Dans 2017 Intelligent Systems Conference (IntelliSys). IEEE, 2017. http://dx.doi.org/10.1109/intellisys.2017.8324210.
Texte intégralRapports d'organisations sur le sujet "Complex systems learning"
Glaser, Donald A. Hierarchical Learning of Complex Systems. Fort Belvoir, VA : Defense Technical Information Center, février 1996. http://dx.doi.org/10.21236/ada312476.
Texte intégralCrawford, Lara S., et S. S. Sastry. Learning Controllers for Complex Behavioral Systems. Fort Belvoir, VA : Defense Technical Information Center, décembre 1996. http://dx.doi.org/10.21236/ada325516.
Texte intégralFaissol, D. Learning Interactions in Complex Biological Systems. Office of Scientific and Technical Information (OSTI), octobre 2019. http://dx.doi.org/10.2172/1573143.
Texte intégralRupe, Adam. Learning Implicit Models of Complex Dynamical Systems From Partial Observations. Office of Scientific and Technical Information (OSTI), juillet 2021. http://dx.doi.org/10.2172/1808822.
Texte intégralScheinberg, Katya. Derivative Free Optimization of Complex Systems with the Use of Statistical Machine Learning Models. Fort Belvoir, VA : Defense Technical Information Center, septembre 2015. http://dx.doi.org/10.21236/ada622645.
Texte intégralSilberstein, Jason, et Marla Spivack. Applying Systems Thinking to Education : Using the RISE Systems Framework to Diagnose Education Systems. Research on Improving Systems of Education (RISE), janvier 2023. http://dx.doi.org/10.35489/bsg-rise-ri_2023/051.
Texte intégralBarjum, Daniel. PDIA for Systems Change : Tackling the Learning Crisis in Indonesia. Research on Improving Systems of Education (RISE), septembre 2022. http://dx.doi.org/10.35489/bsg-rise-ri_2022/046.
Texte intégralHayes, Anne M., Eileen Dombrowski, Allison H. Shefcyk et Jennae Bult. Learning Disabilities Screening and Evaluation Guide for Low- and Middle-Income Countries. RTI Press, avril 2018. http://dx.doi.org/10.3768/rtipress.2018.op.0052.1804.
Texte intégralKaffenberger, Michelle. The Role of Purpose in Education System Outcomes : A Conceptual Framework and Empirical Examples. Research on Improving Systems of Education (RISE), décembre 2022. http://dx.doi.org/10.35489/bsg-risewp_2022/118.
Texte intégralHwa, Yue-Yi, et Lant Pritchett. Teacher Careers in Education Systems That Are Coherent for Learning : Choose and Curate Toward Commitment to Capable and Committed Teachers (5Cs). Research on Improving Systems of Education (RISE), décembre 2021. http://dx.doi.org/10.35489/bsg-rise-misc_2021/02.
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