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Expert Q-learning: Deep Reinforcement Learning with Coarse State Values from Offline Expert Examples
(Peer reviewed; Journal article, 2022)In this article, we propose a novel algorithm for deep reinforcement learning named Expert Q-learning. Expert Q-learning is inspired by Dueling Q-learning and aims to incorporate semi-supervised learning into reinforcement ... -
An expert system for safety instrumented system in petroleum industry
(Master thesis, 2010)The expert system technology has been developed since 1960s and now it has proven to be a useful and effective tool in many areas. It helps shorten the time required to accomplish a certain job and relieve the workload for ... -
Explainable Tsetlin Machine Framework for Fake News Detection with Credibility Score Assessment
(Journal article, 2022)The proliferation of fake news, i.e., news intentionally spread for misinformation, poses a threat to individuals and society. Despite various fact-checking websites such as PolitiFact, robust detection techniques are ... -
Explainable Tsetlin Machine Framework for Fake News Detection with Credibility Score Assessment
(Chapter, 2022)The proliferation of fake news, i.e., news intentionally spread for misinformation, poses a threat to individuals and society. Despite various fact-checking websites such as PolitiFact, robust detection techniques are ... -
Explicit incorporation of spatial variability in a biomass dynamics assessment model
(Peer reviewed; Journal article, 2021) -
Exploration and Performance Analysis of Clustering Algorithms for Time-Series Data with Dimension Reduction
(Master thesis, 2022)Clustering is an attempt to form groups of similar objects, and it is a powerful tool for discovering valuable underlying patterns in the data. When clustering on high dimensional data, the algorithms can suffer from the ... -
Exploration and Performance Analysis of Clustering Algorithms for Time-Series Data with Dimension Reduction
(Master thesis, 2022)Clustering is an attempt to form groups of similar objects, and it is a powerful tool for discovering valuable underlying patterns in the data. When clustering on high dimensional data, the algorithms can suffer from the ... -
An exploration of how social science students utilise an opportunity to learn about simulation-based research methods : A design-based study
(Doctoral Dissertations at the University of Agder; no. 326, Doctoral thesis, 2021)At the core of this thesis lies an exploration of how social science students utilise an opportunity to learn about Modeling and Simulation (M&S)-based research methods. The study is framed within the Cultural Historical ... -
An Exploration of Semi-supervised Text Classification
(Communications in Computer and Information Science;1600, Chapter; Peer reviewed, 2022)Good performance in supervised text classification is usually obtained with the use of large amounts of labeled training data. However, obtaining labeled data is often expensive and time-consuming. To overcome these ... -
An exploration of semi-supervised text classification
(Master thesis, 2021)Obtaining labeled data to train natural language machine learning algorithms is often expensive and time-consuming, while unlabeled data usually is free and easy to get. Frequently a large amount of labeled data ... -
An exploration of teaching and learning activities in mathematics flipped classrooms : A case study in an engineering program
(Doctoral Dissertations at the University of Agder; no. 271, Doctoral thesis, 2020)This research project is a case-study of three consecutive cohorts of engineering students being subject to the pedagogical approach of flipped classroom (Bergmann & Sams, 2012). The study, which is qualitative and based ... -
Exploring Affordances of an Online Environment : A Case-Study of Electronics Engineering Undergraduate Students’ Activity in Mathematics
(Journal article; Peer reviewed, 2019) -
Exploring Changes in Fishery Emissions and Organic Carbon Impacts Associated With a Recovering Stock
(Peer reviewed; Journal article, 2022) -
Exploring grade 9 students' assumption making when mathematizing
(Chapter; Peer reviewed, 2015) -
Exploring Lightweight Deep Learning Solution for Malware Detection in IoT Constraint Environment
(Peer reviewed; Journal article, 2022): The present era is facing the industrial revolution. Machine-to-Machine (M2M) communication paradigm is becoming prevalent. Resultantly, the computational capabilities are being embedded in everyday objects called things. ... -
Exploring Living Nature : Modes of observation in history, teaching and learning
(Doctoral dissertations at University of Agder; no. 449, Doctoral thesis, 2024)The purpose of this study is to phenomenologically explore the practices of observing living nature in history, teaching, and learning, and to discuss potentials and constraints with teaching and learning observational ... -
Exploring Multilingual Word Embedding Alignments in BERT Models: A Case Study of English and Norwegian
(Chapter; Peer reviewed, 2023)Contextual language models, such as transformers, can solve a wide range of language tasks ranging from text classification to question answering and machine translation. Like many deep learning models, the performance ... -
Exploring Realistic Mathematics Education in a Flipped Classroom Context at the Tertiary Level
(Peer reviewed; Journal article, 2020)Flipped classroom (FC) pedagogical frameworks have recently gained considerable popularity, especially at secondary school levels. However, there are rich opportunities to explore FC at tertiary levels, but progress on the ... -
Exploring students’ metacognition in relation to an integral-area evaluation task
(Peer reviewed; Journal article, 2021) -
Exploring Students’ Metacognitive Knowledge: The Case of Integral Calculus
(Peer reviewed; Journal article, 2020)