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Dissertations / Theses on the topic 'Adaptive Learning Systems'

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Published: 4 June 2021

Last updated: 25 July 2025

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1

Holmes, Michael Henry. "Comprehension based adaptive learning systems." Thesis, Manchester Metropolitan University, 2017. http://e-space.mmu.ac.uk/621011/.

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Conversational Intelligent Tutoring Systems aim to mimic the adaptive behaviour of human tutors by delivering tutorial content as part of a dynamic exchange of information conducted using natural language. Deciding when it is beneficial to intervene in a student’s learning process is an important skill for tutoring. Human tutors use prior knowledge about the student, discourse content and learner non-verbal behaviour to choose when intervention will help learners overcome impasse. Experienced human tutors adapt discourse and pedagogy based on recognition of comprehension and non-comprehension

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2

VOLTA, ERICA. "Multisensory learning in adaptive interactive systems." Doctoral thesis, Università degli studi di Genova, 2020. http://hdl.handle.net/11567/1001795.

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The main purpose of my work is to investigate multisensory perceptual learning and sensory integration in the design and development of adaptive user interfaces for educational purposes. To this aim, starting from renewed understanding from neuroscience and cognitive science on multisensory perceptual learning and sensory integration, I developed a theoretical computational model for designing multimodal learning technologies that take into account these results. Main theoretical foundations of my research are multisensory perceptual learning theories and the research on sensory processing and

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3

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<br>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 an

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4

Grundtman, Per. "Adaptive Learning." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-61648.

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The purpose of this project is to develop a novel proof-of-concept system in attempt to measure affective states during learning-tasks and investigate whether machine learning models trained with this data has the potential to enhance the learning experience for an individual. By considering biometric signals from a user during a learning session, the affective states anxiety, engagement and boredom will be classified using different signal transformation methods and finally using machine-learning models from the Weka Java API. Data is collected using an Empatica E4 Wristband which gathers ski

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5

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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6

Rodríguez-Jiménez, Othoniel. "Hierarchical, adaptive learning objects /." free to MU campus, to others for purchase, 2003. http://wwwlib.umi.com/cr/mo/fullcit?p3091962.

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7

Ng, D. T. H. (David Tung Him) 1963 Carleton University Dissertation Computer Science. "Learning systems, adaptive data structures and random environments." Ottawa.:, 1989.

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8

Lindkvist, Emilie. "Learning-by-modeling : Novel Computational Approaches for Exploring the Dynamics of Learning and Self-governance in Social-ecological Systems." Doctoral thesis, Stockholms universitet, Stockholm Resilience Centre, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-122395.

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As a consequence of global environmental change, sustainable management and governance of natural resources face critical challenges, such as dealing with non-linear dynamics, increased resource variability, and uncertainty. This thesis seeks to address some of these challenges by using simulation models. The first line of research focuses on the use of learning-by-doing (LBD) for managing a renewable resource, exemplified by a fish stock, and explores LBD in a theoretical model using artificial intelligence (Paper I and II). The second line of research focuses on the emergence of different fo

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9

Wang, Yu. "Adaptive control and learning using multiple models." Thesis, Yale University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10783473.

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<p> Adaptation can have different objectives. Compared to a learning behavior, which is mainly to optimize the rewards/experience obtained through the learning process, adaptive control is a type of adaptation that follows a specific target guided by a controller. Although the targets may be different, the two types of adaption share common research interests.</p><p> One of the popular research techniques for studying adaptation is the use of multiple models, where the system will utilize information from multiple environment observers instead of one to improve the adaptation behavior in ter

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10

Stackhouse, Christian Paul 1960. "AN ADAPTIVE RULE-BASED SYSTEM." Thesis, The University of Arizona, 1987. http://hdl.handle.net/10150/276534.

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Adaptive systems are systems whose characteristics evolve over time to improve their performance at a task. A fairly new area of study is that of adaptive rule-based systems. The system studied for this thesis uses meta-knowledge about rules, rulesets, rule performance, and system performance in order to improve its overall performance in a problem domain. An interesting and potentially important phenomenon which emerged is that the performance the system learns while solving a problem appears to be limited by an inherent break-even level of complexity. That is, the cost to the system of acqui

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11

Kapp, Marcelo Nepomoceno. "Dynamic optimization of classification systems for adaptive incremental learning." Mémoire, École de technologie supérieure, 2010. http://espace.etsmtl.ca/270/1/KAPP_Marcelo_Nepomoceno.pdf.

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Lors de I'arrivée de nouvelles données, un systeme d'apprentissage incremental se met a jour automatiquement sans reexaminer les anciennes donnees. Lors d'un apprentissage incremental, les parametres des systemes de classification ne sont plus consideres comme invariants puisqu'ils peuvent evolucr en fonction des donnees entrantes. Ces changemcnts causent dcs variations dans I'ajustement des parametres du systeme de classification. Si ces variations sont negligees, la performance finale d'un tel systeme pent etre ulterieurement compromise. De tcls systemes, adaptes au probleme de classif

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Kapp, Marcelo Nepomoceno. "Dynamic optimization of classification systems for adaptive incremental learning." reponame:Repositório Institucional da UNILA, 2016. http://dspace.unila.edu.br/123456789/550.

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Tese de Doutorado, defendida na Université Du Québec, Canadian. 2010<br>Submitted by Nilson Junior (nilson.junior@unila.edu.br) on 2016-05-25T23:32:09Z No. of bitstreams: 2 MKapp_PhD_2010.pdf: 2076219 bytes, checksum: db47dfe0b9ee92594b31d05a2f2e7fef (MD5) Recibo Deposito Legal_TESE_Marcelo Nepomoceno Kapp01.pdf: 205561 bytes, checksum: ac4617abe7f6d68472c1ac6ac02abd26 (MD5)<br>Made available in DSpace on 2016-05-25T23:32:22Z (GMT). No. of bitstreams: 2 MKapp_PhD_2010.pdf: 2076219 bytes, checksum: db47dfe0b9ee92594b31d05a2f2e7fef (MD5) Recibo Deposito Legal_TESE_Marcelo Nepomoceno Kapp01.

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Öfjäll, Kristoffer. "Adaptive Supervision Online Learning for Vision Based Autonomous Systems." Doctoral thesis, Linköpings universitet, Datorseende, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-125916.

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Driver assistance systems in modern cars now show clear steps towards autonomous driving and improvements are presented in a steady pace. The total number of sensors has also decreased from the vehicles of the initial DARPA challenge, more resembling a pile of sensors with a car underneath. Still, anyone driving a tele-operated toy using a video link is a demonstration that a single camera provides enough information about the surronding world. Most lane assist systems are developed for highway use and depend on visible lane markers. However, lane markers may not be visible due to snow or we

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Wang, Olivier. "Adaptive Rules Model : Statistical Learning for Rule-Based Systems." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLX037/document.

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Les Règles Métiers (Business Rules en anglais, ou BRs) sont un outil communément utilisé dans l’industrie pour automatiser des prises de décisions répétitives. Le problème de l’adaptation de bases de règles existantes à un environnement en constante évolution est celui qui motive cette thèse. Des techniques existantes d’Apprentissage Automatique Supervisé peuvent être utilisées lorsque cette adaptation se fait en toute connaissance de la décision correcte à prendre en toute circonstance. En revanche, il n’existe actuellement aucun algorithme, qu’il soit théorique ou pratique, qui puisse résoud

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Serce, Fatma Cemile. "A Multi-agent Adaptive Learning System For Distance Education." Phd thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12609220/index.pdf.

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The adaptiveness provides uniquely identifying and monitoring the learner&rsquo<br>s learning activities according to his/her respective profile. The adaptive intelligent learning management systems (AILMS) help a wide range of students to achieve their learning goals effectively by delivering knowledge in an adaptive or individualized style through online learning settings. This study presents a multi-agent system, called MODA, developed to provide adaptiveness in learning management systems (LMS). A conceptual framework for adaptive learning systems is proposed for this purpose. The framewor

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Madaio, Michael Adam. "Cybernetic autonomy: an analysis and critique of adaptive learning systems." Thesis, Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/53606.

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There has recently been great promise and interest in the use of adaptive learning systems to provide personalized course content, tailored to the ability levels and pace of individual students. Yet, not all the technologies in this space provide the same capabilities. In this thesis I analyze a representative group of adaptive learning providers according to the pedagogical model of their design. Then, I discuss case studies of two systems to analyze their design according to a humanist design philosophy and a more cybernetic design tradition, and I conclude with a set of design guidelines an

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Asri, Layla El. "Learning the Parameters of Reinforcement Learning from Data for Adaptive Spoken Dialogue Systems." Thesis, Université de Lorraine, 2016. http://www.theses.fr/2016LORR0350/document.

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Cette thèse s’inscrit dans le cadre de la recherche sur les systèmes de dialogue. Ce document propose d’apprendre le comportement d’un système à partir d’un ensemble de dialogues annotés. Le système apprend un comportement optimal via l’apprentissage par renforcement. Nous montrons qu’il n’est pas nécessaire de définir une représentation de l’espace d’état ni une fonction de récompense. En effet, ces deux paramètres peuvent être appris à partir du corpus de dialogues annotés. Nous montrons qu’il est possible pour un développeur de systèmes de dialogue d’optimiser la gestion du dialogue en défi

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Asri, Layla El. "Learning the Parameters of Reinforcement Learning from Data for Adaptive Spoken Dialogue Systems." Electronic Thesis or Diss., Université de Lorraine, 2016. http://www.theses.fr/2016LORR0350.

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Cette thèse s’inscrit dans le cadre de la recherche sur les systèmes de dialogue. Ce document propose d’apprendre le comportement d’un système à partir d’un ensemble de dialogues annotés. Le système apprend un comportement optimal via l’apprentissage par renforcement. Nous montrons qu’il n’est pas nécessaire de définir une représentation de l’espace d’état ni une fonction de récompense. En effet, ces deux paramètres peuvent être appris à partir du corpus de dialogues annotés. Nous montrons qu’il est possible pour un développeur de systèmes de dialogue d’optimiser la gestion du dialogue en défi

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Bridle, Robert Angus. "Adaptive user interfaces for mobile computing devices /." View thesis entry in Australian Digital Theses Program, 2008. http://thesis.anu.edu.au/public/adt-ANU20081117.184430/index.html.

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20

Holley, Julian. "Oneiric Machine Learning : The Foundations of Dream Inspired Adaptive Systems." Thesis, University of the West of England, Bristol, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.495516.

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Artificial adaptive systems inspired or derived from neuro-biological components and processes have shown great promise at several levels. One behaviour required for the continuous functional operation of advanced neuro-biological systems is sleep. A definitive function or purpose for sleep and of the associated phenomenology such as dreaming, remains elusive. Correspondingly there remain many unresolved issues within the domain of artificial learning systems. One such aspect that largely remains intractable is the management of experiences once learned and encoded. This is the general problem

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21

Szijarto, Barbara. "Mediating Social Change: Building Adaptive Learning Systems through Developmental Evaluation." Thesis, Université d'Ottawa / University of Ottawa, 2019. http://hdl.handle.net/10393/39159.

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Complex social problems are at the forefront of our awareness. We are witnessing intensifying political, social and environmental challenges and waning confidence in our ability to engineer solutions. We are also seeing a proliferation of large scale, multi-agency interventions that seek change at the level of systems, and through which actors pursue adaptive learning as a means to develop effective solutions. Proponents assert that the prediction and control on which conventional program design and evaluation are based are not available under complex conditions. They propose instead that lear

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22

CERBONI, BAIARDI LORENZO. "Adaptive models of learning in complex physical and social systems." Doctoral thesis, Urbino, 2016. http://hdl.handle.net/11576/2630552.

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23

Guglielmo, Kennon. "A new learning controller for mechanical manipulators applied in Cartesian space." Thesis, Georgia Institute of Technology, 1989. http://hdl.handle.net/1853/17034.

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24

Lapin, Brett Denton. "A learning model adaptive estimator for an automated guided vehicle." Diss., Georgia Institute of Technology, 1993. http://hdl.handle.net/1853/22218.

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25

Chowdhary, Girish. "Concurrent learning for convergence in adaptive control without persistency of excitation." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/37243.

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Model Reference Adaptive Control (MRAC) is a widely studied adaptive control methodology that aims to ensure that a nonlinear plant with significant modeling uncertainty behaves like a chosen reference model. MRAC methods attempt to achieve this by representing the modeling uncertainty as a weighted combination of known nonlinear functions, and using a weight update law that ensures weights take on values such that the effect of the uncertainty is mitigated. If the adaptive weights do arrive at an ideal value that best represent the uncertainty, significant performance and robustness gains can

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26

Shaw, Cole J. (Cole Jim). "System design and architecture of an online, adaptive, and personalized learning platform." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/81128.

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Thesis (S.M. in Technology and Policy)--Massachusetts Institute of Technology, Engineering Systems Division, 2013.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 76-82).<br>The author proposes that personalized learning can be brought to traditional and nontraditional learners through a new type of asynchronous learning platform called Guided Learning Pathways (GLP). The GLP platform allows learners to intelligently traverse a vast field of learning resources, emphasizing content only of direct relevance to the learner and presenting it in a way that matche

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Meccawy, Maram. "A service-orientated architecture for adaptive and collaborative e-learning systems." Thesis, University of Nottingham, 2009. http://eprints.nottingham.ac.uk/10684/.

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This research proposes a new architecture for Adaptive Educational Hypermedia Systems (AEHS). Architectures in the context of this thesis refer to the components of the system and their communications and interactions. The architecture addresses the limitations of AEHS regarding interoperability, reusability, openness, flexibility, and limited tools for collaborative and social learning. It presents an integrated adaptive and collaborative Web-based learning environment. The new e-learning environment is implemented as a set of independent Web services within a service-oriented architecture (S

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Smith, Adalet Serengül Güven. "Application of machine learning algorithms in adaptive web-based information systems." Thesis, Middlesex University, 1999. http://eprints.mdx.ac.uk/6743/.

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Hypertext users often face the difficulty of identifying pages of .information most relevant to their current goals or interests, and are forced to wade through irrelevant pages, even though they know precisely what they are looking for. In order to address this issue, this research has investigated the Technical feasibility and also the utility of applying machine learning algorithms to generate personalised adaptation on the basis of browsing history in hypertext. A Web-based information system called MLTutor has been developed to determine the viability of this approach. The MLTutor has bee

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Лавров, Євгеній Анатолійович, Евгений Анатольевич Лавров, Yevhenii Anatoliiovych Lavrov, N. Rudakova, and N. Barchenko. "Information Technology of Optimization Dialog Interaction for Adaptive E-learning Systems." Thesis, Sumy State University, 2016. http://essuir.sumdu.edu.ua/handle/123456789/47045.

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Лавров, Євгеній Анатолійович, Евгений Анатольевич Лавров, Yevhenii Anatoliiovych Lavrov, E. Kaba, A. Yakovenko, and N. Barchenko. "Information Technology Assessment of Cognitive Comfort for Adaptive E-learning Systems." Thesis, Sumy State University, 2016. http://essuir.sumdu.edu.ua/handle/123456789/47047.

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31

LIUZZO, STEFANO. "Adaptive learning control of nonlinear systems with applications to robot manipulators." Doctoral thesis, Università degli Studi di Roma "Tor Vergata", 2008. http://hdl.handle.net/2108/578.

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The goal of the proposed work is the design of adaptive learning controls for nonlinear systems with output dependent nonlinearities and for robot manipulators. At first, we address the problem of designing an output error feedback control for single input, single output nonlinear systems with uncertain, smooth, output dependent nonlinearities whose local Lipschitz constants are known. The considered systems are required to be observable, minimum phase with known relative degree and known high frequency gain sign: linear systems are included. The reference output signal is assumed to be smoot

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Agbele, Kehinde Kayode. "Context-awareness for adaptive information retrieval systems." Thesis, University of the Western Cape, 2014. http://hdl.handle.net/11394/3845.

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Philosophiae Doctor - PhD<br>This research study investigates optimization of IRS to individual information needs in order of relevance. The research addressed development of algorithms that optimize the ranking of documents retrieved from IRS. In this thesis, we present two aspects of context-awareness in IR. Firstly, the design of context of information. The context of a query determines retrieved information relevance. Thus, executing the same query in diverse contexts often leads to diverse result rankings. Secondly, the relevant context aspects should be incorporated in a way that support

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Gil, de la Iglesia Didac. "A Formal Approach for Designing Distributed Self-Adaptive Systems." Doctoral thesis, Linnéuniversitetet, Institutionen för medieteknik (ME), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-34195.

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Engineering contemporary distributed software applications is a challenging task due to the dynamic operating conditions in which these systems have to function. Examples are dynamic availability of resources, errors that are difficult to predict, and changing user requirements. These dynamics can affect a number of quality concerns of a system, such as robustness, openness, and performance. The challenges of engineering software systems with such dynamics have motivated the need for self-adaptation. Self-adaptation is based on the principle of separation of concerns, distinguishing two well d

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Ziemann, Ingvar. "Applications of Information Inequalities to Linear Systems : Adaptive Control and Security." Licentiate thesis, KTH, Reglerteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-291203.

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This thesis considers the application of information inequalities, Cramér-Rao type bounds, based on Fisher information, to linear systems. These tools are used to study the trade-offs between learning and performance in two application areas: adaptive control and control systems security. In the first part of the thesis, we study stochastic adaptive control of linear quadratic regulators (LQR). Here, information inequalities are used to derive instance-dependent regret lower bounds. First, we consider a simplified version of LQR, a memoryless reference tracking model, and show how regret can

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Jörneskog, Gustav, and Josef Kandelan. "Using Deep Reinforcement Learning For Adaptive Traffic Control in Four-Way Intersections." Thesis, Linköpings universitet, Kommunikations- och transportsystem, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-158204.

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The consequences of traffic congestion include increased travel time, fuel consumption, and the number of crashes. Studies suggest that most traffic delays are due to nonrecurring traffic congestion. Adaptive traffic control using real-time data is effective in dealing with nonrecurring traffic congestion. Many adaptive traffic control algorithms used today are deterministic and prone to human error and limitation. Reinforcement learning allows the development of an optimal traffic control policy in an unsupervised manner. We have implemented a reinforcement learning algorithm that only requir

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Moreno, Cavidad Julian. "Reference model for adaptive and intelligent educational systems supported by learning objects." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2012. http://hdl.handle.net/10183/70222.

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A aprendizagem assistida por computador, conhecida mais amplamente com o nome genérico de e-learning, converteu-se numa poderosa ferramenta com amplas potencialidades dentro do campo educativo. Mesmo assim, uma das maiores críticas que esta recebe é que na maioria dos casos os cursos que são implementados seguem um enfoque “one size fits all”, isto é, que todos os alunos recebem exatamente o mesmo conteúdo e da mesma maneira desconhecendo suas necessidades particulares. Esta falha radica não só na falta de interação direita entre aluno e tutor, senão também na falta de um desenho instrucional

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Cho, Sukhwan. "A Learning Control, Intervention Strategy for Location-Aware Adaptive Vehicle Dynamics Systems." Diss., Virginia Tech, 2015. http://hdl.handle.net/10919/74422.

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The focus of Location-Aware Adaptive Vehicle Dynamics System (LAAVDS) research is to develop a system to avoid situations in which the vehicle exceeds its handling capabilities. The proposed method is predictive, estimating the ability of the vehicle to successfully navigate upcoming terrain, and it is assumed that the future vehicle states and local driving environment is known. An Intervention Strategy must be developed such that the vehicle is navigated successfully along a road via modest changes to the driver's commands and do so in a manner that is in harmony with the driver's intentio

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Lesh, Neal. "Scalable and adaptive goal recognition /." Thesis, Connect to this title online; UW restricted, 1998. http://hdl.handle.net/1773/6897.

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Almohammadi, Khalid. "Type-2 fuzzy logic based systems for adaptive learning and teaching within intelligent e-learning environments." Thesis, University of Essex, 2016. http://repository.essex.ac.uk/17211/.

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The recent years have witnessed an increased interest in e-learning platforms that incorporate adaptive learning and teaching systems that enable the creation of adaptive learning environments to suit individual student needs. The efficiency of these adaptive educational systems relies on the methodology used to accurately gather and examine information pertaining to the characteristics and needs of students and relies on the way that information is processed to form an adaptive learning context. The vast majority of existing adaptive educational systems do not learn from the users’ behaviours

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Janarthanam, Srinivasan Chandrasekaran. "Learning user modelling strategies for adaptive referring expression generation in spoken dialogue systems." Thesis, University of Edinburgh, 2011. http://hdl.handle.net/1842/5033.

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We address the problem of dynamic user modelling for referring expression generation in spoken dialogue systems, i.e how a spoken dialogue system should choose referring expressions to refer to domain entities to users with different levels of domain expertise, whose domain knowledge is initially unknown to the system. We approach this problem using a statistical planning framework: Reinforcement Learning techniques in Markov Decision Processes (MDP). We present a new reinforcement learning framework to learn user modelling strategies for adaptive referring expression generation (REG) in resou

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Machado, Guilherme Medeiros. "AwARE : an approach for adaptive recommendation of resources." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2018. http://hdl.handle.net/10183/175081.

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Sistemas de recomendação foram propostos no início da década de 1990 com o objetivo de auxiliar seus usuários a lidar com a sobrecarga cognitiva criada com o advento da internet e o aumento constante de documentos. De lá para cá tais sistemas passaram a assumir vários outros papéis, tais como “auxiliar usuários a explorar”, “melhorar a tomada de decisão”, ou até mesmo “entreter”. Para atingir tais novos objetivos, o sistema necessita olhar para características do usuário que auxiliem no entendimento da tarefa desempenhada pelo usuário e como a recomendação pode auxiliar tal tarefa. Nesse senti

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Scheuer, Oliver [Verfasser], and Armin [Akademischer Betreuer] Weinberger. "Towards adaptive argumentation learning systems : theoretical and practical considerations in the design of argumentation learning systems / Oliver Scheuer. Betreuer: Armin Weinberger." Saarbrücken : Saarländische Universitäts- und Landesbibliothek, 2015. http://d-nb.info/1077211619/34.

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Arnao, Luis Maza, Ibañez Carlos Arturo Raymundo, and Francisco Dominguez. "Modelo de asociación entre objetos y estilos de aprendizajes para una Plataforma de aprendizaje adaptativo." International Institute of Informatics and Systemics, IIIS, 2017. http://hdl.handle.net/10757/622494.

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Septima Conferencia Iberoamericana de Complejidad, Informatica y Cibernetica, CICIC 2017 - 7th Ibero-American Conference on Complexity, Informatics and Cybernetics, CICIC 2017; Orlando; United States; 21 March 2017 through 24 March 2017; Code 131437<br>Adaptive learning systems constitute a new approach to e-learning systems, they allow adapting the content to the individual characteristics of students. Two of its main components are the domain model and the student model, whose key elements are the learning objects (OA) and learning style, respectively. LOs are digital educational content pro

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Gómez, Ardila Sergio Eduardo. "Learning design implementation in context-aware and adaptive mobile learning." Doctoral thesis, Universitat de Girona, 2013. http://hdl.handle.net/10803/116492.

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Mobile learning (m-learning) is still in its infancy, and great efforts should be made so as to investigate the potentials of an educational paradigm shift from the traditional one-size-fits-all teaching approaches to an adaptive learning that can be delivered via mobile devices. Thus, the next challenge has been identified from this implication: How learning design can be implemented so as to benefit from the m-learning characteristics and achieve adaptation and personalization of the individual learning process in different contexts? An important factor for achieving personalized and adaptiv

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Jordaan, Edzard Adolf Biermann. "Intelligent elevator control based on adaptive learning and optimisation." Thesis, Stellenbosch : Stellenbosch University, 2014. http://hdl.handle.net/10019.1/95999.

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Thesis (MEng)--Stellenbosch University, 2014.<br>ENGLISH ABSTRACT: Machine learning techniques have been around for a few decades now and are being established as a pre-dominant feature in most control applications. Elevators create a unique control application where traffic flow is controlled and directed according to certain control philosophies. Machine learning techniques can be implemented to predict and control every possible traffic flow scenario and deliver the best possible solution. Various techniques will be implemented in the elevator application in an attempt to establish a

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Weeraprajak, Issarest. "Faster Adaptive Network Based Fuzzy Inference System." Thesis, University of Canterbury. Mathematics and Statistics, 2007. http://hdl.handle.net/10092/1234.

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It has been shown by Roger Jang in his paper titled "Adaptive-network-based fuzzy inference systems" that the Adaptive Network based Fuzzy Inference System can model nonlinear functions, identify nonlinear components in a control system, and predict a chaotic time series. The system use hybrid-learning procedure which employs the back-propagation-type gradient descent algorithm and the least squares estimator to estimate parameters of the model. However the learning procedure has several shortcomings due to the fact that * There is a harmful and unforeseeable influence of the size of the pa

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Erdogmus, Deniz. "Information theoretic learning Renyi's entropy and its applications to adaptive system training /." [Gainesville, Fla.] : University of Florida, 2002. http://purl.fcla.edu/fcla/etd/UFE1000122.

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Thesis (Ph. D.)--University of Florida, 2002.<br>Title from title page of source document. Document formatted into pages; contains xv, 217 p.; also contains graphics. Includes vita. Includes bibliographical references.

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Shafi, Kamran Information Technology &amp Electrical Engineering Australian Defence Force Academy UNSW. "An online and adaptive signature-based approach for intrusion detection using learning classifier systems." Awarded by:University of New South Wales - Australian Defence Force Academy, 2008. http://handle.unsw.edu.au/1959.4/38991.

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This thesis presents the case of dynamically and adaptively learning signatures for network intrusion detection using genetic based machine learning techniques. The two major criticisms of the signature based intrusion detection systems are their i) reliance on domain experts to handcraft intrusion signatures and ii) inability to detect previously unknown attacks or the attacks for which no signatures are available at the time. In this thesis, we present a biologically-inspired computational approach to address these two issues. This is done by adaptively learning maximally general rules, whic

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Marriot, Shaun. "The application of adaptive resonance theory and reinforcement learning to mapping and control." Thesis, University of Sheffield, 1996. http://etheses.whiterose.ac.uk/5974/.

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In this thesis, the ideas of Adaptive Resonance Theory (ART) and Reinforcement Learning (RL) are applied to the problems of mapping and control. A neural architecture, fuzzy ARTMAP is considered as an alternative to standard feedforward networks for noisy mapping tasks. It is one of a series of architectures based upon ART. Fuzzy ARTMAP has advantages over feedforward networks--such as increased autonomy- and is especially suited to classification-type problems. Here it is used to estimate a continuous mapping from noisy data. Results show that properties useful for classification problems are

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Yang, Shanhu. "An Adaptive Prognostic Methodology and System Framework for Engineering Systems under Dynamic Working Regimes." University of Cincinnati / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1455209450.

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