Blar i AURA på forfatter "Andersen, Per-Arne"
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Active network management with decision transformer
Åsvestad, Vegard; Sevland, Ruben (Master thesis, 2024)This thesis analyzes the implementation of a DT model for ANM in power grids, focusing on active network management with intermittent renewable energy sources. Considering the increasing implementation of renewable sources ... -
Active Network Management with Decision Transformer
Sevland, Ruben; Svensli Åsvestad, Vegard (Master thesis, 2024)This thesis analyzes the implementation of a DT model for ANM in power grids, focusing on active network management with intermittent renewable energy sources. Considering the increasing implementation of renewable sources ... -
Advancements in Safe Deep Reinforcement Learning for Real-Time Strategy Games and Industry Applications
Andersen, Per-Arne (Doctoral dissertations at the University of Agder;361, Doctoral thesis, 2022) -
Advancing IoT Security with Tsetlin Machines: A Resource-Efficient Anomaly Detection Approach
Thorsen, Henning Blomfeldt; Gunvaldsen, Ole (Master thesis, 2023)The number of IoT devices are rapidly increasing, and the nature of the devices leave them vulnerable to attacks. As of today there are no general security solutions that meet the requirements of running with limited ... -
Advancing IoT Security with Tsetlin Machines: A Resource-Efficient Anomaly Detection Approach
Gunvaldsen, Ole; Thorsen, Henning Blomfeldt (Master thesis, 2023)The number of IoT devices are rapidly increasing, and the nature of the devices leave them vulnerable to attacks. As of today there are no general security solutions that meet the requirements of running with limited ... -
Analyzing the performance of transformers for streamflow prediction
Hindersland, Jonatan Hertzberg (Master thesis, 2023)Within the field of hydrology, there is a vital need to be able to predict streamflow values from hydrological basins. This has traditionally been done through physics and mathematics-based models, where measured data are ... -
Deep Q-Learning With Q-Matrix Transfer Learning for Novel Fire Evacuation Environment
Sharma, Jivitesh; Andersen, Per-Arne; Granmo, Ole-Christoffer; Goodwin, Morten (Journal article; Peer reviewed, 2020) -
Deep Reinforcement Learning using Capsules in Advanced Game Environments
Andersen, Per-Arne; Goodwin, Morten; Granmo, Ole-Christoffer (Master thesis, 2018)Reinforcement Learning (RL) is a research area that has blossomed tremendously in recent years and has shown remarkable potential for artificial intelligence based opponents in computer games. This success is primarily due ... -
Deep Reinforcement Learning using Capsules in Advanced Game Environments
Andersen, Per-Arne (Master thesis, 2017)Reinforcement Learning (RL) is a research area that has blossomed tremendously in recent years and has shown remarkable potential for arti cial intelligence based opponents in computer games. This success is primarily due ... -
Development of a Novel Object Detection System Based on Synthetic Data Generated from Unreal Game Engine
Rasmussen, Ingeborg; Kvalsvik, Sigurd; Andersen, Per-Arne; Aune, Teodor N.; Hagen, Daniel (Peer reviewed; Journal article, 2022)This paper presents a novel approach to training a real-world object detection system based on synthetic data utilizing state-of-the-art technologies. Training an object detection system can be challenging and time-consuming ... -
FlashRL: A Reinforcement Learning Platform for Flash Games
Andersen, Per-Arne; Goodwin, Morten; Granmo, Ole-Christoffer (Journal article; Peer reviewed, 2017) -
Increasing sample efficiency in deep reinforcement learning using generative environment modelling
Andersen, Per-Arne; Goodwin, Morten; Granmo, Ole-Christoffer (Journal article; Peer reviewed, 2020) -
MapAI: Precision in BuildingSegmentation
Jyhne, Sander; Goodwin, Morten; Andersen, Per-Arne; Oveland, Ivar; Nossum, Alexander Salveson; Ormseth, Karianne Øydegard; Ørstavik, Mathilde; Flatman, Andrew C. (Peer reviewed; Journal article, 2022)MapAI: Precision in Building Segmentation is a competition arranged with the Norwegian Artificial Intelligence Research Consortium (NORA) 1 in collaboration with Centre for Artificial Intelligence Research at the University ... -
The Dreaming Variational Autoencoder for Reinforcement Learning Environments
Andersen, Per-Arne; Goodwin, Morten; Granmo, Ole-Christoffer (Journal article; Peer reviewed, 2018)Reinforcement learning has shown great potential in generalizing over raw sensory data using only a single neural network for value optimization. There are several challenges in the current state-of-the-art reinforcement ... -
The Potential and Limitations of the Tsetlin Machine in Model-Free Reinforcement Learning
Grimsmo, Andreas; Drøsdal, Didrik Kallhovd (Master thesis, 2023)This paper aims to investigate the potential of model-free reinforcement learning using the Tsetlin Machine by evaluating its performance in widely recognized benchmark environments for reinforcement learning: Cartpole and ... -
The Potential and Limitations of the Tsetlin Machine in Model-Free Reinforcement Learning
Drøsdal, Didrik Kallhovd; Grimsmo, Andreas (Master thesis, 2023)This paper aims to investigate the potential of model-free reinforcement learning using the Tsetlin Machine by evaluating its performance in widely recognized benchmark environments for reinforcement learning: Cartpole and ... -
Towards safe reinforcement-learning in industrial grid-warehousing
Andersen, Per-Arne; Goodwin, Morten; Granmo, Ole-Christoffer (Peer reviewed; Journal article, 2020) -
Transformer Reinforcement Learning for Procedural Level Generation
Mrozik, Lukasz Filip; Aas, Sebastian Bekkvik (Master thesis, 2023)This paper examines how recent advances in sequence modeling translate for machine learning assisted procedural level generation. We explore the use of Transformer based models like DistilGPT-2 to generate platformer levels, ... -
Transformer Reinforcement Learning for Procedural Level Generation
Mrozik, Lukasz Filip; Aas, Sebastian Bekkvik (Master thesis, 2023)This paper examines how recent advances in sequence modeling translate for machine learning assisted procedural level generation. We explore the use of Transformer based models like DistilGPT-2 to generate platformer levels, ... -
Utilizing Reinforcement Learning and Computer Vision in a Pick-And-Place Operation for Sorting Objects in Motion
Solberg, Trygve Andre Olsøy; Sand, Kristoffer (Master thesis, 2023)This master's thesis studies the implementation of advanced machine learning (ML) techniques in industrial automation systems, focusing on applying machine learning to enable and evolve autonomous sorting capabilities in ...