Sökning: "Adaptive learning"

Visar resultat 1 - 5 av 210 avhandlingar innehållade orden Adaptive learning.

1. 1. Learning Together, Leading Change : Understanding Collective Learning in Social Entrepreneurial Organisations

   Författare :Morteza Eslahchi; Ali Osman; Maria Gustavsson; Stockholms universitet; []
   Nyckelord :SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; collective learning; social entrepreneurial organisations; social entrepreneurship; social entrepreneur; social innovation; communities of practice; Sweden; COVID-19 pandemic; pedagogik; Education;

   Sammanfattning : This dissertation aims to generate an understanding of collective learning in social entrepreneurial organisations in Sweden, especially during the COVID-19 pandemic. Employing a collective learning-centred perspective, I want to explore the following key areas: a) the learning conditions and organising processes entailed in becoming a social entrepreneur and creating a social entrepreneurial organisation, b) the importance of collective learning for organisational adaptation and change in tackling exogenous factors such as the COVID-19 pandemic, and c) the role of leadership in creating conditions conducive to collective learning processes in social entrepreneurial organisations during the COVID-19 pandemic. LÄS MER

3. 2. Learning-by-modeling : Novel Computational Approaches for Exploring the Dynamics of Learning and Self-governance in Social-ecological Systems

   Författare :Emilie Lindkvist; Maja Schlüter; Jon Norberg; Örjan Ekeberg; James Dyke; Stockholms universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; Complex adaptive systems; Renewable resources; Adaptive management; Small-scale fisheries; Artificial intelligence; Reinforcement learning; Agent-based modeling; agent-baserade modeller; artificiell intelligens; social-ekologiska system; komplexa adaptiva system; förnyelsebara naturresurser; adaptiv förvaltning; Sustainability Science; vetenskap om hållbar utveckling;

   Sammanfattning : 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. LÄS MER

4. 3. Sharing to learn and learning to share : Fitting together metalearning and multi-task learning

   Författare :Richa Upadhyay; Marcus Liwicki; Ronald Phlypo; Rajkumar Saini; Atsuto Maki; Luleå tekniska universitet; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Multi-task learning; Meta learning; transfer learning; knowledge sharing algorithms; Machine Learning; Maskininlärning;

   Sammanfattning : This thesis focuses on integrating learning paradigms that ‘share to learn,’ i.e., Multitask Learning (MTL), and ‘learn (how) to share,’ i.e. LÄS MER

5. 4. Towards Robust and Adaptive Machine Learning : A Fresh Perspective on Evaluation and Adaptation Methodologies in Non-Stationary Environments

   Författare :Firas Bayram; Bestoun S. Ahmed; Patrick Glauner; Karlstads universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; machine learning; concept drift; covariate shift; performance robustness; evaluation methodology; adaptive learning; Computer Science; Datavetenskap;

   Sammanfattning : Machine learning (ML) has become ubiquitous in various disciplines and applications, serving as a powerful tool for developing predictive models to analyze diverse variables of interest. With the advent of the digital era, the proliferation of data has presented numerous opportunities for growth and expansion across various domains. LÄS MER

7. 5. Approaches to Interactive Online Machine Learning

   Författare :Agnes Tegen; Paul Davidsson; Jan A. Persson; Henrik Boström; Malmö universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Machine Learning; Interactive Machine Learning; Online Learning; Active Learning; Machine Teaching;

   Sammanfattning : With the Internet of Things paradigm, the data generated by the rapidly increasing number of connected devices lead to new possibilities, such as using machine learning for activity recognition in smart environments. However, it also introduces several challenges. LÄS MER