Sökning: "agent learning"

Visar resultat 1 - 5 av 120 avhandlingar innehållade orden agent learning.

  1. 1. Adding Challenge to a Teachable Agent in a Virtual Learning Environment

    Författare :Camilla Kirkegaard; Agneta Gulz; Annika Silvervarg; Björn Johansson; Lena Pareto; Linköpings universitet; []
    Nyckelord :SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; educational technology; educational software; teachable agents; learning;

    Sammanfattning : The topic of this thesis concerns what happens when challenging behavior is added to a teachable agent in a virtual learning environment. The aim of adding challenging behavior to teachable agents is to encourage students to engage in learning behaviors, improve their motivation and engagement, which may result in a deeper level of comprehension and an improved learning experience. 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. A Learning-driven Approach for Behavior Modeling in Agent-based Simulation

    Författare :Robert Junges; Franziska Klügl; Mathias Broxvall; Lars Braubach; Örebro universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; agent-based simulation; agent modeling; agent learning;

    Sammanfattning : Agent-based simulation is a prominent application of the agent-based system metaphor. One of the main characteristics of this simulation paradigm is the generative nature of the outcome: the macro-level system behavior is generated from the micro-level agent behavior. LÄS MER

  5. 4. Mot en ny vuxenutbildningspolitik? : Regional utveckling som policy och praktik

    Författare :Erik Jakobsson; Per-Erik Ellström; Lennart Svensson; Kjell Rubensson; Linköpings universitet; []
    Nyckelord :SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; adult learning; adult education; planning; learning; institution; structure; agent; network; collaboration; case study; interactive research; policy; practice; reform; implementation; vuxnas lärande; vuxenutbildning; nätverk; samverkan; fallstudie; interaktiv forskning; policy; praktik; reform; implementering; planering; lärande; institution; struktur; agent; Education; Pedagogik;

    Sammanfattning : Avhandlingen beskriver och analyserar ett regionalt utvecklingsinitiativ i nätverksform, genom vilket de kommunala lärcentrumen i Örebro län samverkar för att utveckla en gemensam infrastruktur för vuxnas lärande. Detta innebär, exempelvis, att utveckla former för samverkan mellan olika regionala aktörer inom området, öka samordningen och samverkan inom den kommunala vuxenutbildningen och utveckla metoder för lärande med fokus på arbetet och arbetsplatsen. LÄS MER

  7. 5. Data-Efficient Learning of Semantic Segmentation

    Författare :David Nilsson; Mathematical Imaging Group; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; semantic segmentation; embodied learning; active learning; semantic video segmentation; computer vision; deep learning;

    Sammanfattning : Semantic segmentation is a fundamental problem in visual perception with a wide range of applications ranging from robotics to autonomous vehicles, and recent approaches based on deep learning have achieved excellent performance. However, to train such systems there is in general a need for very large datasets of annotated images. LÄS MER