Relevant bibliographies by topics / Complex Systems Learning Environments

Academic literature on the topic 'Complex Systems Learning Environments'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Complex Systems Learning Environments"

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Jovancevic, J., B. Sullivan, and M. Hayhoe. "Learning gaze allocation priorities in complex environments." Journal of Vision 6, no. 6 (March 19, 2010): 480. http://dx.doi.org/10.1167/6.6.480.

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Moglia, M., K. S. Alexander, and A. Sharma. "Discussion of the enabling environments for decentralised water systems." Water Science and Technology 63, no. 10 (May 1, 2011): 2331–39. http://dx.doi.org/10.2166/wst.2011.443.

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Decentralised water supply systems are becoming increasingly affordable and commonplace in Australia and have the potential to alleviate urban water shortages and reduce pollution into natural receiving marine and freshwater streams. Learning processes are necessary to support the efficient implementation of decentralised systems. These processes reveal the complex socio-technical and institutional factors to be considered when developing an enabling environment supporting decentralised water and wastewater servicing solutions. Critical to the technological transition towards established decentralised systems is the ability to create strategic and adaptive capacity to promote learning and dialogue. Learning processes require institutional mechanisms to ensure the lessons are incorporated into the formulation of policy and regulation, through constructive involvement of key government institutions. Engagement of stakeholders is essential to the enabling environment. Collaborative learning environments using systems analysis with communities (social learning) and adaptive management techniques are useful in refining and applying scientists' and managers' knowledge (knowledge management).
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Liu, Zhe, Zhijian Qiao, Chuanzhe Suo, Yingtian Liu, and Kefan Jin. "Map-less long-term localization in complex industrial environments." Assembly Automation 41, no. 6 (October 4, 2021): 714–24. http://dx.doi.org/10.1108/aa-06-2021-0088.

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Purpose This paper aims to study the localization problem for autonomous industrial vehicles in the complex industrial environments. Aiming for practical applications, the pursuit is to build a map-less localization system which can be used in the presence of dynamic obstacles, short-term and long-term environment changes. Design/methodology/approach The proposed system contains four main modules, including long-term place graph updating, global localization and re-localization, location tracking and pose registration. The first two modules fully exploit the deep-learning based three-dimensional point cloud learning techniques to achieve the map-less global localization task in large-scale environment. The location tracking module implements the particle filter framework with a newly designed perception model to track the vehicle location during movements. Finally, the pose registration module uses visual information to exclude the influence of dynamic obstacles and short-term changes and further introduces point cloud registration network to estimate the accurate vehicle pose. Findings Comprehensive experiments in real industrial environments demonstrate the effectiveness, robustness and practical applicability of the map-less localization approach. Practical implications This paper provides comprehensive experiments in real industrial environments. Originality/value The system can be used in the practical automated industrial vehicles for long-term localization tasks. The dynamic objects, short-/long-term environment changes and hardware limitations of industrial vehicles are all considered in the system design. Thus, this work moves a big step toward achieving real implementations of the autonomous localization in practical industrial scenarios.
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Davis, Susan. "Activity systems analysis methods: understanding complex learning environments, by Lisa C. Yamagata-Lynch." Pedagogies: An International Journal 7, no. 1 (January 2012): 95–99. http://dx.doi.org/10.1080/1554480x.2012.630575.

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Li, Shoulin, and Weiya Guo. "Supervised Reinforcement Learning for ULV Path Planning in Complex Warehouse Environment." Wireless Communications and Mobile Computing 2022 (October 14, 2022): 1–12. http://dx.doi.org/10.1155/2022/4384954.

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The rapid development of the logistics industry leads to an urgent need for intelligent equipment to improve warehouse transportation efficiency. Recent advances in unmanned logistics vehicles (ULVs) make them particularly important in smart warehouses. However, the complex warehouse environment poses a significant challenge to ULV transportation path planning. Multiple ULVs need to transport cargoes with good coordination ability to overcome the low efficiency of a single ULV. The ULVs also need to interact with the environment to achieve optimal path planning with obstacle avoidance. In this paper, we propose a supervised deep reinforcement learning (SDRL) approach for logistics warehouses that enables autonomous ULVs path planning for cargo transportation in a complex environment. The proposed SDRL approach is featured by (1) designing the supervision module to imitate the behaviors of experts and thus improve the coordination ability of multiple ULVs, (2) optimizing the generator of the imitation learning based on the proximal policy optimization to boost the learning performance, and (3) developing the policy module via deep reinforcement learning to avoid obstacles when navigating the ULVs in warehouse environments. The experiments over dynamic and fixed-point warehouse environments show that the proposed SDRL approach outperforms its rivals regarding average reward, training speed, task completion rate, and collision times.
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Jacobson, Michael J., and Rand J. Spiro. "Hypertext Learning Environments, Cognitive Flexibility, and the Transfer of Complex Knowledge: An Empirical Investigation." Journal of Educational Computing Research 12, no. 4 (June 1995): 301–33. http://dx.doi.org/10.2190/4t1b-hbp0-3f7e-j4pn.

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Although the use of hypertext systems for learning complex knowledge has been attracting recent attention, we currently have poor theoretical and research perspectives from which to understand special characteristics associated with learning in nonlinear and multidimensional hypertext instructional systems. A study was conducted to investigate a theory-based hypertext learning environment that provided instruction in a complex and ill-structured domain. The experimental treatment incorporated several features derived from recent cognitive learning theory, in particular a hypertext procedure that presented the instructional material in multiple contexts to highlight different facets of the knowledge. The main results of the study revealed that although the control treatment led to higher performance on the measures of memory for factual knowledge, the more hypertext-like treatment promoted superior knowledge transfer. Overall, these findings suggest hypertext learning environments that present the instructed knowledge by explicitly demonstrating critical interrelationships between abstract and case-specific knowledge components in multiple contexts will help prepare students to use knowledge in new ways and in new situations.
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Kordova, Sigal. "Developing systems thinking in a Project-Based Learning environment." International Journal of Engineering Education 2, no. 1 (June 15, 2020): 63–81. http://dx.doi.org/10.14710/ijee.2.1.63-81.

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As science and engineering projects are becoming increasingly more complex, sophisticated, comprehensive and multidisciplinary, there is a growing need for systems thinking skills to ensure successful project management. Systems thinking plays a major role in the initiation, effective management, and in facilitating inter-organizational tasks. This research assesses the capacity for engineering systems thinking and its contribution in carrying out a multidisciplinary project. The research also reviews the cognitive process through which systems thinking skill is acquired. The study focused on a group of students who have completed their senior design projects in high-tech industry, while their plans were being integrated into existing larger projects in the respective industrial sites. The systems thinking skill of the students was examined according to a questionnaire for assessing the Capacity for Engineering Systems Thinking (CEST). Statistical analysis shows significant differences in the students capacity for systems thinking at the beginning and end of the work (p<0.001). This research demonstrates that systems thinking skills can be improved through awareness and involvement in multidisciplinary projects.
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Schofield, Damian. "Guidelines for Learning : Using 3D Interactive Systems for Education and Training." Journal on Interactive Systems 3, no. 1 (June 15, 2012): 1. http://dx.doi.org/10.5753/jis.2012.609.

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Advanced 3D virtual environment technology, similar to that used by the film and computer games industry can allow educational developers to rapidly create realistic 3D, virtual environments. This technology has been used to generate a range of interactive learning environments across a broad spectrum of industries and educational application areas. Virtual Reality (VR) simulators represent a powerful tool for learning and teaching. The idea is not new. Flight simulators have been used for decades to train pilots for both commercial and military aviation. These systems have advanced to a point that they are integral to both the design and the operation of modern aircraft [1, 2]. There are a number of lessons that can be learned from other industries that have successfully utilised virtual training and learning systems for a number of years. Generic rules of thumb regarding the specification, development, application and operation of these learning environments can be garnered from other industrial training systems and examined in an educational context [3, 4, 5]. This paper will introduce a virtual learning environment which has been developed by the authors. During the implementation of this, and other, visual learning environments a number of complex operational problems have been encountered, these have required a number of innovative solutions and management procedures to be developed. The paper will also discuss the implementation of these systems and extrapolate the lessons learnt into general guidelines to be considered for the development of VR based educational learning resources. These guidelines will then be discussed in the context of the development of ViRILE (Virtual Reality Interactive Learning Environment). This software is designed for use by undergraduate chemical engineers and simulates the configuration and operation of a polymerisation plant.
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Verster, Belinda, and Carolien van den Berg. "Theorising With Sociomateriality: Interdisciplinary Collaboration in Socio-Technical Learning Environments." Educational Research for Social Change 11, no. 2 (October 28, 2022): 1–18. http://dx.doi.org/10.17159/2221-4070/2021/v11i2a3.

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In this paper, we explore the possibilities offered by sociomateriality for academics to engage with complex learning environments. The focus is on a longitudinal design-based research (DBR) study that includes an interdisciplinary, collaborative student project between Information Systems (IS) and Urban Planning (URP) from two different higher education institutions in Cape Town, South Africa. In the project, student groups collaborate to find potential digital innovations for sustainability challenges in their local communities. The aim is to position the student as an active community member with intimate knowledge of local sustainability challenges, and to develop social digital innovations for the benefit of local communities. We apply sociomateriality as a theoretical lens to rethink socio-technical learning environments and propose four pedagogical propositions of relationality, reflexivity, responsiveness, and recognition to guide the pedagogical decision-making when designing complex learning environments. We conclude the paper by mapping student reflections and experiences to the four pedagogical propositions to illustrate how the theoretical sociomaterial elements translate into the learning environment.
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Villalba-Díez, Javier, Martin Molina, Joaquín Ordieres-Meré, Shengjing Sun, Daniel Schmidt, and Wanja Wellbrock. "Geometric Deep Lean Learning: Deep Learning in Industry 4.0 Cyber–Physical Complex Networks." Sensors 20, no. 3 (January 30, 2020): 763. http://dx.doi.org/10.3390/s20030763.

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In the near future, value streams associated with Industry 4.0 will be formed by interconnected cyber–physical elements forming complex networks that generate huge amounts of data in real time. The success or failure of industry leaders interested in the continuous improvement of lean management systems in this context is determined by their ability to recognize behavioral patterns in these big data structured within non-Euclidean domains, such as these dynamic sociotechnical complex networks. We assume that artificial intelligence in general and deep learning in particular may be able to help find useful patterns of behavior in 4.0 industrial environments in the lean management of cyber–physical systems. However, although these technologies have meant a paradigm shift in the resolution of complex problems in the past, the traditional methods of deep learning, focused on image or video analysis, both with regular structures, are not able to help in this specific field. This is why this work focuses on proposing geometric deep lean learning, a mathematical methodology that describes deep-lean-learning operations such as convolution and pooling on cyber–physical Industry 4.0 graphs. Geometric deep lean learning is expected to positively support sustainable organizational growth because customers and suppliers ought to be able to reach new levels of transparency and traceability on the quality and efficiency of processes that generate new business for both, hence generating new products, services, and cooperation opportunities in a cyber–physical environment.
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Dissertations / Theses on the topic "Complex Systems Learning Environments"

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AlZahrani, Saleh Saeed. "Regionally distributed architecture for dynamic e-learning environment (RDADeLE)." Thesis, De Montfort University, 2010. http://hdl.handle.net/2086/3814.

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e-Learning is becoming an influential role as an economic method and a flexible mode of study in the institutions of higher education today which has a presence in an increasing number of college and university courses. e-Learning as system of systems is a dynamic and scalable environment. Within this environment, e-learning is still searching for a permanent, comfortable and serviceable position that is to be controlled, managed, flexible, accessible and continually up-to-date with the wider university structure. As most academic and business institutions and training centres around the world have adopted the e-learning concept and technology in order to create, deliver and manage their learning materials through the web, it has become the focus of investigation. However, management, monitoring and collaboration between these institutions and centres are limited. Existing technologies such as grid, web services and agents are promising better results. In this research a new architecture has been developed and adopted to make the e-learning environment more dynamic and scalable by dividing it into regional data grids which are managed and monitored by agents. Multi-agent technology has been applied to integrate each regional data grid with others in order to produce an architecture which is more scalable, reliable, and efficient. The result we refer to as Regionally Distributed Architecture for Dynamic e-Learning Environment (RDADeLE). Our RDADeLE architecture is an agent-based grid environment which is composed of components such as learners, staff, nodes, regional grids, grid services and Learning Objects (LOs). These components are built and organised as a multi-agent system (MAS) using the Java Agent Development (JADE) platform. The main role of the agents in our architecture is to control and monitor grid components in order to build an adaptable, extensible, and flexible grid-based e-learning system. Two techniques have been developed and adopted in the architecture to build LOs' information and grid services. The first technique is the XML-based Registries Technique (XRT). In this technique LOs' information is built using XML registries to be discovered by the learners. The registries are written in Dublin Core Metadata Initiative (DCMI) format. The second technique is the Registered-based Services Technique (RST). In this technique the services are grid services which are built using agents. The services are registered with the Directory Facilitator (DF) of a JADE platform in order to be discovered by all other components. All components of the RDADeLE system, including grid service, are built as a multi-agent system (MAS). Each regional grid in the first technique has only its own registry, whereas in the second technique the grid services of all regional grids have to be registered with the DF. We have evaluated the RDADeLE system guided by both techniques by building a simulation of the prototype. The prototype has a main interface which consists of the name of the system (RDADeLE) and a specification table which includes Number of Regional Grids, Number of Nodes, Maximum Number of Learners connected to each node, and Number of Grid Services to be filled by the administrator of the RDADeLE system in order to create the prototype. Using the RST technique shows that the RDADeLE system can be built with more regional grids with less memory consumption. Moreover, using the RST technique shows that more grid services can be registered in the RDADeLE system with a lower average search time and the search performance is increased compared with the XRT technique. Finally, using one or both techniques, the XRT or the RST, in the prototype does not affect the reliability of the RDADeLE system.
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Collins, Jayne-Louise. "System learning in complex and emergent environments: A study of how leaders in one education system enabled capacity for learning focused on the enactment of moral purpose." Thesis, Australian Catholic University, 2016. https://acuresearchbank.acu.edu.au/download/fdd4a61d52c7a4b13f1eb2a06858e8d44f9ae1660e6392d284d50a90d54b67f6/73775935/201601_Jayne_Louise_Collins.pdf.

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This thesis explores system capacity building, in particular, the purpose of system capacity building and how leaders, in the context of Leading for Learning Project, enabled whole of system capacity building with a focus on sustained engagement with moral purpose. It is argued, however, that the purpose and scope of system capacity building is often conceptually limited because it is understood within the current regulatory and performance focused education reform environment. This thesis, therefore, offers an alternative perspective by engaging with the theoretical underpinnings of complexity theory. As such, this thesis offers a conceptualisation of education systems as complex adaptive systems and system capacity building as a complex and emergent process. The thesis presents a radical reframing of education systems arguing that education systems are better understood as open, dynamic, and emergent systems, constituted of many interdependent relationships throughout the system.
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Barris, Coralie Sian. "An examination of learning design in elite springboard diving." Thesis, Queensland University of Technology, 2013. https://eprints.qut.edu.au/63807/1/Coralie_Barris_Thesis.pdf.

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The overarching aim of this programme of work was to evaluate the effectiveness of the existing learning environment within the Australian Institute of Sport (AIS) elite springboard diving programme. Unique to the current research programme, is the application of ideas from an established theory of motor learning, specifically ecological dynamics, to an applied high performance training environment. In this research programme springboard diving is examined as a complex system, where individual, task, and environmental constraints are continually interacting to shape performance. As a consequence, this thesis presents some necessary and unique insights into representative learning design and movement adaptations in a sample of elite athletes. The questions examined in this programme of work relate to how best to structure practice, which is central to developing an effective learning environment in a high performance setting. Specifically, the series of studies reported in the chapters of this doctoral thesis: (i) provide evidence for the importance of designing representative practice tasks in training; (ii) establish that completed and baulked (prematurely terminated) take-offs are not different enough to justify the abortion of a planned dive; and (iii), confirm that elite athletes performing complex skills are able to adapt their movement patterns to achieve consistent performance outcomes from variable dive take-off conditions. Chapters One and Two of the thesis provide an overview of the theoretical ideas framing the programme of work, and include a review of literature pertinent to the research aims and subsequent empirical chapters. Chapter Three examined the representativeness of take-off tasks completed in the two AIS diving training facilities routinely used in springboard diving. Results highlighted differences in the preparatory phase of reverse dive take-offs completed by elite divers during normal training tasks in the dry-land and aquatic training environments. The most noticeable differences in dive take-off between environments began during the hurdle (step, jump, height and flight) where the diver generates the necessary momentum to complete the dive. Consequently, greater step lengths, jump heights and flight times, resulted in greater board depression prior to take-off in the aquatic environment where the dives required greater amounts of rotation. The differences observed between the preparatory phases of reverse dive take-offs completed in the dry-land and aquatic training environments are arguably a consequence of the constraints of the training environment. Specifically, differences in the environmental information available to the athletes, and the need to alter the landing (feet first vs. wrist first landing) from the take-off, resulted in a decoupling of important perception and action information and a decomposition of the dive take-off task. In attempting to only practise high quality dives, many athletes have followed a traditional motor learning approach (Schmidt, 1975) and tried to eliminate take-off variations during training. Chapter Four examined whether observable differences existed between the movement kinematics of elite divers in the preparation phases of baulked (prematurely terminated) and completed take-offs that might justify this approach to training. Qualitative and quantitative analyses of variability within conditions revealed greater consistency and less variability when dives were completed, and greater variability amongst baulked take-offs for all participants. Based on these findings, it is probable that athletes choose to abort a planned take-off when they detect small variations from the movement patterns (e.g., step lengths, jump height, springboard depression) of highly practiced comfortable dives. However, with no major differences in coordination patterns (topology of the angle-angle plots), and the potential for negative performance outcomes in competition, there appears to be no training advantage in baulking on unsatisfactory take-offs during training, except when a threat of injury is perceived by the athlete. Instead, it was considered that enhancing the athletes' movement adaptability would be a more functional motor learning strategy. In Chapter Five, a twelve-week training programme was conducted to determine whether a sample of elite divers were able to adapt their movement patterns and complete dives successfully, regardless of the perceived quality of their preparatory movements on the springboard. The data indeed suggested that elite divers were able to adapt their movements during the preparatory phase of the take-off and complete good quality dives under more varied take-off conditions; displaying greater consistency and stability in the key performance outcome (dive entry). These findings are in line with previous research findings from other sports (e.g., shooting, triple jump and basketball) and demonstrate how functional or compensatory movement variability can afford greater flexibility in task execution. By previously only practising dives with good quality take-offs, it can be argued that divers only developed strong couplings between information and movement under very specific performance circumstances. As a result, this sample was sometimes characterised by poor performance in competition when the athletes experienced a suboptimal take-off. Throughout this training programme, where divers were encouraged to minimise baulking and attempt to complete every dive, they demonstrated that it was possible to strengthen the information and movement coupling in a variety of performance circumstances, widening of the basin of performance solutions and providing alternative couplings to solve a performance problem even when the take-off was not ideal. The results of this programme of research provide theoretical and experimental implications for understanding representative learning design and movement pattern variability in applied sports science research. Theoretically, this PhD programme contributes empirical evidence to demonstrate the importance of representative design in the training environments of high performance sports programmes. Specifically, this thesis advocates for the design of learning environments that effectively capture and enhance functional and flexible movement responses representative of performance contexts. Further, data from this thesis showed that elite athletes performing complex tasks were able to adapt their movements in the preparatory phase and complete good quality dives under more varied take-off conditions. This finding signals some significant practical implications for athletes, coaches and sports scientists. As such, it is recommended that care should be taken by coaches when designing practice tasks since the clear implication is that athletes need to practice adapting movement patterns during ongoing regulation of multi-articular coordination tasks. For example, volleyball servers can adapt to small variations in the ball toss phase, long jumpers can visually regulate gait as they prepare for the take-off, and springboard divers need to continue to practice adapting their take-off from the hurdle step. In summary, the studies of this programme of work have confirmed that the task constraints of training environments in elite sport performance programmes need to provide a faithful simulation of a competitive performance environment in order that performance outcomes may be stabilised with practice. Further, it is apparent that training environments can be enhanced by ensuring the representative design of task constraints, which have high action fidelity with the performance context. Ultimately, this study recommends that the traditional coaching adage 'perfect practice makes perfect", be reconsidered; instead advocating that practice should be, as Bernstein (1967) suggested, "repetition without repetition".
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Pelliciari, Marcos Roberto de Mendonça. "A liderança do docente como elo integrador no processo ensino-aprendizagem baseado em problemas (Problem-Based Learning) em ambientes híbridos na engenharia." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/18/18157/tde-02052013-161901/.

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Muitas instituições de ensino superior (IES) buscam novas formas de aperfeiçoarem o processo ensino-aprendizagem visando adequarem as aulas tradicionais às tecnologias emergentes advindas da Web 2.0, como as mídias sociais. Nesse processo de reinvenção, o docente deve capacitar-se a ministrar aulas não apenas com o intuito de disseminar conhecimentos tácitos e explícitos, mas também de liderar os estudantes na sala de aula presencial e nos ambientes virtuais de aprendizagem, conduzindo-os a superarem suas expectativas quanto ao aprendizado. Analisando perfis de liderança existentes, a presente dissertação, focada em um Estudo de Caso, busca identificar qual o perfil ideal de liderança do docente em ambientes híbridos, utilizando-se para tal do Índice de Satisfação de Grupo, análise de gráficos e do discurso dos estudantes. O método de ensino adotado pelo docente foi o PBL (Problem Based Learning), dando-se ênfase ao desenvolvimento do pensamento critico. A pesquisa realizou-se junto a disciplinas do Departamento de Engenharia de Produção da EESC-USP, onde estudantes de graduação e pós-graduação foram desafiados pelo método PBL a pensarem de forma crítica na construção do próprio conhecimento. Os resultados obtidos por meio de questionários aplicados ao final dos semestres de 2011 e 2012 mostram que a liderança Laissez-faire não é indicada na fase de implantação do PBL, necessitando maior interferência do docente para a quebra do paradigma entre o modelo de ensino tradicional e o novo. Conclui-se que a conexão entre o processo ensino-aprendizagem tradicional e o novo possa ser feita por meio da liderança situacional, alternando a liderança transformacional e a transacional de acordo com o contexto, excluindo-se a Laissez-faire.
Many institutions have developed new ways to improve the teaching-learning process, trying to adequate the classes to the emerging new technologies based on Web 2.0, as in the case of social media. In this re-inventing process teachers must have the leadership skills both in classrooms and virtual learning environments, allowing the students to overcome their expectations of the learning process. This dissertation is focused on a case study that seeks to identify what is the ideal leadership profile into hybrid environments, using a group satisfaction index, graphical analysis and student speeching skills. The teaching methodology used by the teacher was the PBL (Problem-Based Learning) that emphasizes the critical mindset. The research was carried out during the disciplines into the Manufacturing Engineering graduation and post-graduation program of Universidade de São Paulo (USP) EESC department. The students were challenged by the PBL methodology to think about the best way to build their own know how. The data obtained with the application of questionaries in the 2011 and 2012 semesters showed that the \"Laissez-Faire\" leadership is not recommended during the PBL methodology implementation, requiring more interferences and attention from the teacher to break the paradigm of the traditional teaching models. The conclusion is that the connection between the traditional and the new teaching-learning processes can be built using situational leadership, alternating between transformational leadership and transactional models, contextually, excluding the Laissez-faire.
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Corrêa, Ygor. "O agir linguageiro na perspectiva dos sistemas adaptativos complexos em ambiente virtual de aprendizagem em EAD." Universidade do Vale do Rio dos Sinos, 2014. http://www.repositorio.jesuita.org.br/handle/UNISINOS/3850.

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UNISINOS - Universidade do Vale do Rio dos Sinos
O presente estudo concebe o papel central da língua no desenvolvimento humano por meio de um agir linguageiro. Nessa perspectiva, compreende-se que a linguagem se situa em práticas interacionais e está em permanente transformação. Este estudo tem caráter empírico de cunho qualitativo, inserido na plataforma Moodle, investigando a especificidade das interações realizadas em Chats, em uma disciplina de Ensino à Distância (EAD) na perspectiva da Teoria da Complexidade (GLEICK, 1994; JOHNSON 2003; LARSENFREEMAN 1997, 2008, 2009; MORIN 2008) e do Interacionismo Sociodiscursivo - ISD (BRONCKART, 1999, 2008). A compreensão epistemológica deste estudo abarca o agir humano em desenvolvimento caracterizado como um sistema adaptativo complexo. Sendo que, a partir das práticas de nível mais baixo, mas não menos complexas, os comportamentos acabam por emergir. Assim, os interagentes desenvolvem comportamentos observáveis que emergem das condições iniciais, encaminhando-se às manifestações de auto-organização. O agir humano situado na plataforma, assim como as práticas situadas por meio de tipos específicos de discursos (BRONCKART, 1999) estão entendidos como geradores de movimentos de complexidade. As relações discursivas tecnologicamente situadas foram observadas quanto à forma como os interagentes se adaptavam ao contexto discursivo. A partir das interações analisadas, elencaram-se, então, tipos de discurso e foram propostos quatro tipos de Movimentos de Complexidade que emergiram das interações discursivas: Movimento 1 – Dinamicidade discursiva entre interagentes; Movimento 2 – Não-linearidade interacional; Movimento 3 – Adaptação de agentividade (espaço-tempo) e Movimento 4 – Comportamento emergente. A análise do agir linguageiro, situado por meio de tipos de discurso identificados, apresentou baixo índice de variação da escrita em linguagem formal; como era de se esperar, dado o caráter formal da troca entre pares. O estudo permitiu evidenciar que os tipos de discurso se adaptam na medida em que os interagentes passam por mudanças interacionais de fases co-construídas em processo, alternando entre os tipos de discurso relato interativo e relato misto interativo-teórico pela ausência do discurso teórico.
This study conceives the central role of language in the human development through language acting. In this perspective, it is comprehended that language is situated in interactional practices and it is permanently transformed. This study has an empirical character and a qualitative approach, inserted in the Moodle platform, investigating the specificity of the interactions made in Chats in a Distance Learning Environment according to the Complexity Theory perspective (GLEICK, 1989; JOHNSON 2003; LARSEN-FREEMAN 1997, 2008, 2009; MORIN 2008) and the Sociodiscursive Interactionism perspective (BRONCKART, 1999, 2008). The epistemological comprehension of this study considers that the language acting under development is characterized as a complex adaptive system, in which behaviors eventually emerge from practices of lower level, but not less complex. Then, the interactants develop observing behaviors that emerge from the initial conditions, heading towards self-organization manifestations. The situated language acting on the platform, as well as the situated practices through specific types of discourse (BRONCKART, 2008), are understood as generators of complexity movements. The ways interactants adapted themselves to the discursive context were observed as discursive relations technologically situated. From the analyzed interactions, types of discourse were established and four types of complexity movements, which emerged from the discursive interactions, were proposed: Movement 1 – Discursive Dynamics among interactants; Movement 2 – Non-Interactional linearity; Movement 3 – Agentivity Adaptation (space-time); Movement 4 – Emergent Behavior. The analysis of the situated language acting, through identified types of discourse, presented a low rate of variation in formal language use, as it was expected, due to the formal character of the exchange among pairs. The study allowed us to evidence that the types of discourse are adaptable as the interactants go through phases of interactional change coconstructed in process, alternating between interactive-reporting and mixed theoreticalinteractive types of discourse, by the absence of theoretical discourse.
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Eriksson, Oskar, and Mattias Larsson. "Increasingly Complex Environments in Deep Reinforcement Learning." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-259193.

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In this thesis, we used deep reinforcement learning to train autonomous agents and evaluated the impact of increasing the complexity of the training environment over time. This was compared to using a fixed complexity. Also, we investigated the impact of using a pre-trained agent as a starting point for training in an environment with a different complexity, compared to an untrained agent. The scope was limited to only training and analyzing agents playing a variant of the 2D game Snake. Random obstacles were placed on the map, and complexity corresponds to the amount of obstacles. Performance was measured in terms of eaten fruits. The results showed benefits in overall performance for the agent trained in increasingly complex environments. With regard to previous research, it was concluded that this seems to hold generally, but more research is needed on the topic. Also, the results displayed benefits of using a pre-trained model as a starting point for training in a different complexity environment, which was hypothesized.
I denna studie använde vi deep reinforcement learning för att träna autonoma agenter och utvärderade inverkan av att använda miljöer med ökande komplexitet över tid. Detta jämfördes med att använda en fixerad komplexitet. Utöver detta jämförde vi att använda en tränad agent som startpunkt för träning i en miljö med en annan komplexitet, jämfört med att använda en otränad agent. Studien avgränsades till att bara träna och analysera agenter på en variant av 2D-spelet Snake. Hinder placerades slumpmässigt ut på kartan, och komplexiteten motsvarar antalet hinder. Prestationen mättes i antal frukter som agenten lyckades äta. Resultaten visade att agenten som tränades i miljöer med ökande komplexitet presterade bättre totalt sett. Med hänsyn till tidigare forskning drogs slutsatsen att detta verkar vara ett generellt fenomen, men att mer forskning behövs på ämnet. Vidare visade resultaten att det finns fördelar med att använda en redan tränad agent som startpunkt för träning i en miljö med en annan komplexitet, vilket var en del av författarnas hypotes.
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Ullah, Hassan Qudrat. "Decision making and learning in complex dynamic environments /." [S.l.] : [s.n.], 2002. http://aleph.unisg.ch/hsgscan/hm00250491.pdf.

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Aitkenhead, Matthew. "Using artificial intelligence to model complex systems." Thesis, University of Aberdeen, 2003. http://digitool.abdn.ac.uk/R?func=search-advanced-go&find_code1=WSN&request1=AAIU602065.

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Two observations underpin this thesis; 1. There is a need for automated pattem-recognition techniques that allow processes requiring skills normally associated with the human brain to be carried out rapidly, reliably and cheaply, and; 2. The current methods applied to solving artificial intelligence (AI) problems are insufficient to the task of creating generalised systems capable of pattem-recognition and environmental interaction. Neural networks (NNs) are a good method of solving AI problems that are difficult or impossible to solve using knowledge-based or symbolic techniques. NNs provide the flexibility to analyse poorly-defined systems or systems that are general in nature, and also provide the ability to learn from noisy, complex data sets. The main problem with the use of NNs to date has been that one NN's structure and dynamics may work for a specific problem, but if this problem is changed slightly then it is difficult to determine the optimal settings for the network to enable it to adapt to the new situation. The use of evolutionary methods is emphasised throughout this thesis as a way of optimising NN system performance. Several methods have been developed through the course of this thesis that improve the performance of NN models. One of the most important is the use of a biologically plausible node and connection modification algorithm. In this method, local effects such as the activation levels of nodes at either end of a connection or a node's past activation history are the only input parameters which network components use for their adjustment. Included in the biological plausibility argument are NN structuring methods that mimic specific areas of the brain. One example is the visual system, in which a pyramidal structure is applied that permits a hierarchical pattern recognition process to develop. This process builds the image recognition up from small 'substructures' in successive layers, allowing the system to recognise objects that are not specifically defined by the user. Arguments are made that an AI systems's utility is limited if it does not have the capability of interacting with its environment. A system that merely observes without attempting to alter or exist within an environment is only half of the story. From a biological standpoint, intelligence is the result of successive generations of organisms interacting with and altering their environment. Limiting an AI system's ability to interact with the environment can only place restrictions on the capabilities of that system, not improve them. Following development of a suite of applicable pattem-recognition techniques, work is carried out in order to implement these methods within a simple environment. For the moment, a virtual 'block world' is used that is relatively easy and cheap to manipulate. The importance of both modularity and sensory feedback to the ability to develop complex behaviours is investigated, with these two concepts included in the overall evolutionary strategy of system development. The results obtained show that the techniques developed provide a pattem- recognition and learning system that is capable of being applied to general problems and that learns without human intervention. In comparison to classical NN techniques the systems developed show superior learning abilities and can be applied in less specific situations. The use of modularity and sensory feedback in the animat simulations has allowed the development of behavioural patterns that are difficult to achieve using homogeneous, input-output systems. Evolutionary methods have allowed system optimisation in a way that is impossible to achieve through trial and error, and which also permit the system to be easily fine-tuned towards specific problems and situations. With current advances in computer speed and memory capacity, it is now possible to implement NNs comparable in size to the nervous systems of small animals. The methods used here provide the potential to provide these NNs with the sophistication displayed by their organic counterparts.
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Hurst, Jacob Machar. "Learning classifier systems in robotic environments." Thesis, University of the West of England, Bristol, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.274088.

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Allison, Colin. "Systems support for distributed learning environments." Thesis, University of St Andrews, 2003. http://hdl.handle.net/10023/14519.

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This thesis contends that the growing phenomena of multi-user networked "learning environments" should be treated as distributed interactive systems and that their developers should be aware of the systems and networks issues involved in their construction and maintenance. Such environments are henceforth referred to as distributed learning environments, or DLEs. Three major themes are identified as part of systems support: i) shared resource coherence in DLEs; ii) Quality of Service for the end- users of DLEs; and iii) the need for an integrating framework to develop, deploy and manage DLEs. The thesis reports on several distinct implementations and investigations that are each linked by one or more of those themes. Initially, responsiveness and coherence emerged as potentially conflicting requirements, and although a system was built that successfully resolved this conflict it proved difficult to move from the "clean room" conditions of a research project into a real world learning context. Accordingly, subsequent systems adopted a web-based approach to aid deployment in realistic settings. Indeed, production versions of these systems have been used extensively in credit-bearing modules in several Scottish Universities. Interactive responsiveness then emerged as a major Quality of Service issue in its own right, and motivated a series of investigations into the sources of delay, as experienced by end users of web-oriented distributed learning environments. Investigations into this issue provided insight into the nature of web-oriented interactive distributed learning and highlighted the need to be QoS-aware. As the volume and the range of usage of distributed learning applications increased the need for an integrating framework emerged. This required identifying and supporting a wide variety of educational resource types and also the key roles occupied by users of the system, such as tutors, students, supervisors, service providers, administrators, examiners. The thesis reports on the approaches taken and lessons learned from researching, designing and implementing systems which support distributed learning. As such, it constitutes a documented body of work that can inform the future design and deployment of distributed learning environments.
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Books on the topic "Complex Systems Learning Environments"

1

Nurcan, Selmin, and Elias Pimenidis, eds. Information Systems Engineering in Complex Environments. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19270-3.

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Isaías, Pedro, J. Michael Spector, Dirk Ifenthaler, and Demetrios G. Sampson, eds. E-Learning Systems, Environments and Approaches. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-05825-2.

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Grigoʹevich, Ivakhnenko Alekseĭ, ed. Inductive learning algorithms for complex systems modeling. Boca Raton: CRC Press, 1994.

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M, Duffy Thomas, Lowyck Joost, Jonassen David H. 1947-, and NATO Advanced Research Workshop on The Design of Constructivist Learning Environments: Implications for Instructional Design and the Use of Technology (1991 : Catholic University of Leuven), eds. Designing environments for constructive learning. Berlin: Springer-Verlag, 1993.

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Multiteam systems: An organization form for dynamic and complex environments. New York: Routledge, 2011.

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Tolk, Andreas, and Lakhmi C. Jain, eds. Complex Systems in Knowledge-based Environments: Theory, Models and Applications. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-88075-2.

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C, Jain L., Tolk Andreas, and SpringerLink (Online service), eds. Complex Systems in Knowledge-based Environments: Theory, Models and Applications. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009.

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Kramarov, Sergey, Vladimir Khramov, Elena Grebenyuk, and Anatoly Bocharov. Fundamentals of the ergotechnical approach to the formation of an electronic educational environment. ru: Publishing Center RIOR, 2021. http://dx.doi.org/10.29039/02086-9.

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The monograph deals with the problems of analysis and synthesis of electronic information and learning environment as an ergatic system. The issues of creation, development and evaluation of such systems, as well as information support of the process of building and using artificial intelligence, including in the protection of information, are considered. The monograph provides theoretical justifications for the research of information objects, which reveals the mechanism of constructing a mathematical model of the educational process at the university and explains the understanding of the education system as a system of systems, as well as information processes associated with it. The research presented in the monograph is the basis for the creation of new and effective robotic organizational and organizational-technical systems in education. The monograph is intended for researchers and teachers, postgraduates, undergraduates and engineers specializing in the field of educational management, including intelligent adaptive control of complex robotic systems.
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Shute, Valerie J. A comparison of learning environments: All that glitters--. Brooks Air Force Base, Tex: Armstrong Laboratory, Air Force Systems Command, 1992.

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NATO Advanced Research Workshop on Instructional Models in Computer-Based Learning Environments (1991 University of Twente). Instructional models in computer-based learning environments. Berlin: Springer-Verlag, 1992.

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Book chapters on the topic "Complex Systems Learning Environments"

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Mandl, Heinz, Hans Gruber, and Alexander Renkl. "Knowledge Application in Complex Systems." In Technology-Based Learning Environments, 40–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-79149-9_6.

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Kim, Daniel H. "Learning Laboratories: Designing a Reflective Learning Environment." In Computer-Based Management of Complex Systems, 327–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-74946-9_34.

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Friedman, Eric J. "Asynchronous Learning in Decentralized Environments: A Game-Theoretic Approach." In Collectives and the Design of Complex Systems, 133–43. New York, NY: Springer New York, 2004. http://dx.doi.org/10.1007/978-1-4419-8909-3_4.

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Grabaskas, Nathaniel, and Zhizhen Wang. "Intrinsic Rewards for Reinforcement Learning Within Complex 2D Environments." In Lecture Notes in Networks and Systems, 425–37. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-82193-7_28.

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Baker, Patrick, and Kay Fielden. "Complex Clusters in Local Environments: Multi-Layered Multi-Media Learning." In Systems Theory and Practice in the Knowledge Age, 391–98. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0601-0_45.

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Zhang, Xu, Felix Lütteke, Christian Ziegler, and Jörg Franke. "Self-learning RRT* Algorithm for Mobile Robot Motion Planning in Complex Environments." In Intelligent Autonomous Systems 13, 57–69. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-08338-4_5.

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Zhong, Ying, Yiran Zhu, Zhiliang Wang, Xia Yin, Xingang Shi, and Keqin Li. "An Adversarial Learning Model for Intrusion Detection in Real Complex Network Environments." In Wireless Algorithms, Systems, and Applications, 794–806. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59016-1_65.

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Cleveland, Benjamin. "Innovative Learning Environments as Complex Adaptive Systems: Enabling Middle Years’ Education." In Transforming Education, 55–78. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-5678-9_4.

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Dever, Daryn A., and Roger Azevedo. "Scaffolding Self-regulated Learning in Game-Based Learning Environments Based on Complex Systems Theory." In Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium, 41–46. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-11647-6_7.

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Long, Rodney A., Jennifer M. Riley, and Christina K. Padron. "Using Mobile Technology to Generate Learning Content for an Intelligent Tutoring System." In Augmented Cognition. Enhancing Cognition and Behavior in Complex Human Environments, 199–209. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58625-0_14.

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Conference papers on the topic "Complex Systems Learning Environments"

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Baneres, David, and Joaquin Saiz. "Intelligent Tutoring System for Learning Digital Systems on MOOC Environments." In 2016 10th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS). IEEE, 2016. http://dx.doi.org/10.1109/cisis.2016.47.

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Behjat, Amir, Hemanth Manjunatha, Prajit Krisshna Kumar, Apurv Jani, Leighton Collins, Payam Ghassemi, Joseph Distefano, et al. "Learning Robot Swarm Tactics over Complex Adversarial Environments." In 2021 International Symposium on Multi-Robot and Multi-Agent Systems (MRS). IEEE, 2021. http://dx.doi.org/10.1109/mrs50823.2021.9620707.

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Rodriguez, Pilar, Alvaro Ortigosa, and Rosa M. Carro. "Extracting Emotions from Texts in E-Learning Environments." In 2012 Sixth International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS). IEEE, 2012. http://dx.doi.org/10.1109/cisis.2012.192.

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Austin, Ron, Mak Sharma, Philip Moore, and David Newell. "Situated Computing and Virtual Learning Environments: e-Learning and the Benefits to the Students Learning." In 2013 7th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS). IEEE, 2013. http://dx.doi.org/10.1109/cisis.2013.95.

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Takadama, Keiki, Daichi Yamazaki, Masaya Nakata, and Hiroyuki Sato. "Complex-Valued-based Learning Classifier System for POMDP Environments." In 2019 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2019. http://dx.doi.org/10.1109/cec.2019.8790083.

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Frey, Jonas, David Hoeller, Shehryar Khattak, and Marco Hutter. "Locomotion Policy Guided Traversability Learning using Volumetric Representations of Complex Environments." In 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2022. http://dx.doi.org/10.1109/iros47612.2022.9982190.

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Orlando, De Pietro, and Frontera Giovanni. "An Integrated System, with Natural Language Management, for the Monitoring Activities in e-Learning Environments." In 2008 International Conference on Complex, Intelligent and Software Intensive Systems. IEEE, 2008. http://dx.doi.org/10.1109/cisis.2008.137.

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Han, Wanbin, Chongrong Fang, and Jianping He. "Mapless Path Planning of Multi-robot Systems in Complex Environments via Deep Reinforcement Learning." In 2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS). IEEE, 2022. http://dx.doi.org/10.1109/docs55193.2022.9967756.

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Xu, Zihao, Juan Cao, and Zhangli Lan. "On Highway Guardrail Segmentation Algorithms Based on Patrol Car Mobile Video in Complex Environments." In 2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS). IEEE, 2020. http://dx.doi.org/10.1109/ddcls49620.2020.9275123.

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Caballé, Santi, Fatos Xhafa, and Ajith Abraham. "A Replication-Based Approach for the Improvement of the Online Learning Experience in Distributed Environments." In 2009 International Conference on Complex, Intelligent and Software Intensive Systems (CISIS). IEEE, 2009. http://dx.doi.org/10.1109/cisis.2009.18.

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Reports on the topic "Complex Systems Learning Environments"

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Glaser, Donald A. Hierarchical Learning of Complex Systems. Fort Belvoir, VA: Defense Technical Information Center, February 1996. http://dx.doi.org/10.21236/ada312476.

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Korotun, Olha V., Tetiana A. Vakaliuk, and Vladimir N. Soloviev. Model of using cloud-based environment in training databases of future IT specialists. [б. в.], July 2020. http://dx.doi.org/10.31812/123456789/3865.

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The authors substantiates and develops the model of using cloud-based environment (CBE) in the training of databases of future information technology (IT) specialists, which consists of interrelated units: target (purpose, task of using CBE), conceptual (pedagogical approaches, didactic principles), organizational and semantic (characteristics of CBE, basic requirements for CBE, subjects of training, CBE of the teacher, CBE of the student, curricula of institution of higher education, educational-methodical complex of discipline “Databases”, installation and configuration of database management system, development of educational material from the database in electronic form, selection of cloud-based systems of distance learning, introduction of cloud-based systems of distance learning in the training of students’ databases, selection of CBE in database training (databases, forms, methods, tools), evaluative (criteria, indicators, levels of professional and practical competence of future IT specialists on the use of CBE in database training), effective (increased formation of the information and communication technologies of future IT specialists on the use of CBE in database training).
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Crawford, Lara S., and S. S. Sastry. Learning Controllers for Complex Behavioral Systems. Fort Belvoir, VA: Defense Technical Information Center, December 1996. http://dx.doi.org/10.21236/ada325516.

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Faissol, D. Learning Interactions in Complex Biological Systems. Office of Scientific and Technical Information (OSTI), October 2019. http://dx.doi.org/10.2172/1573143.

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Mitter, Sanjoy K. Environments for Modeling and Simulation of Complex Systems. Fort Belvoir, VA: Defense Technical Information Center, June 1998. http://dx.doi.org/10.21236/ada394745.

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Dullerud, Geir E. Hybrid Control for Multi-Agent Systems in Complex Sensing Environments. Fort Belvoir, VA: Defense Technical Information Center, February 2012. http://dx.doi.org/10.21236/ada567715.

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McBurnie, Chris. The use of virtual learning environments and learning management systems during the COVID-19 pandemic. EdTech Hub, May 2020. http://dx.doi.org/10.53832/edtechhub.0023.

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Rupe, Adam. Learning Implicit Models of Complex Dynamical Systems From Partial Observations. Office of Scientific and Technical Information (OSTI), July 2021. http://dx.doi.org/10.2172/1808822.

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Kolgatin, Oleksandr H., Larisa S. Kolgatina, Nadiia S. Ponomareva, and Ekaterina O. Shmeltser. Systematicity of students’ independent work in cloud learning environment. [б. в.], September 2019. http://dx.doi.org/10.31812/123456789/3247.

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The paper deals with the problem of out-of-class students’ independent work in information and communication learning environment based on cloud technologies. Results of appropriate survey among students of pedagogical university are discussed. The students answered the questions about systematicity of their learning activity and propositions for its improving. It is determined that the leading problems are needs in more careful instruction according to features of the task completing, insufficient experience in self-management, the lack of internal motivation. Most of all, students recommend to provide the tasks with detail instruction (oral or written) and to pay attention to careful planning the time that is necessary for full completion of the task. It is pointed that such complicated requirements can be satisfied only by complex use of information and communication technologies as well as the automated system of pedagogical diagnostics. Some requirements for management of students’ out-of-classroom independent work are formulated as a result of this discussion.
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Hovakimyan, Naira, Hunmin Kim, Wenbin Wan, and Chuyuan Tao. Safe Operation of Connected Vehicles in Complex and Unforeseen Environments. Illinois Center for Transportation, August 2022. http://dx.doi.org/10.36501/0197-9191/22-016.

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Autonomous vehicles (AVs) have a great potential to transform the way we live and work, significantly reducing traffic accidents and harmful emissions on the one hand and enhancing travel efficiency and fuel economy on the other. Nevertheless, the safe and efficient control of AVs is still challenging because AVs operate in dynamic environments with unforeseen challenges. This project aimed to advance the state-of-the-art by designing a proactive/reactive adaptation and learning architecture for connected vehicles, unifying techniques in spatiotemporal data fusion, machine learning, and robust adaptive control. By leveraging data shared over a cloud network available to all entities, vehicles proactively adapted to new environments on the proactive level, thus coping with large-scale environmental changes. On the reactive level, control-barrier-function-based robust adaptive control with machine learning improved the performance around nominal models, providing performance and control certificates. The proposed research shaped a robust foundation for autonomous driving on cloud-connected highways of the future.
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