Adaptive Task Assignment in Online Learning Environments. - Per-Arne Andersen; Christian Kråkevik; Morten Goodwin; Anis Yazidi (WIMS, 2016)

FlashRL: A Reinforcement Learning Platform for Flash Games. - Per-Arne Andersen; Morten Goodwin; Ole-Christoffer Granmo (NIK, 2017)

Towards a Deep Reinforcement Learning Approach for Tower Line Wars. - Per-Arne Andersen; Morten Goodwin; Ole-Christoffer Granmo (SGAI Conf., 2017)

Deep RTS: A Game Environment for Deep Reinforcement Learning in Real-Time Strategy Games. - Per-Arne Andersen; Morten Goodwin; Ole-Christoffer Granmo (CIG, 2018)

The Dreaming Variational Autoencoder for Reinforcement Learning Environments. - Per-Arne Andersen; Morten Goodwin; Ole-Christoffer Granmo (SGAI Conf., 2018)

Deep Reinforcement Learning using Capsules in Advanced Game Environments. - Per-Arne Andersen (CoRR, 2018)

Towards Model-Based Reinforcement Learning for Industry-Near Environments. - Per-Arne Andersen; Morten Goodwin; Ole-Christoffer Granmo (SGAI Conf., 2019)

Interpretable Option Discovery Using Deep Q-Learning and Variational Autoencoders. - Per-Arne Andersen; Morten Goodwin; Ole-Christoffer Granmo (INTAP, 2020)

Safer Reinforcement Learning for Agents in Industrial Grid-Warehousing. - Per-Arne Andersen; Morten Goodwin; Ole-Christoffer Granmo (LOD (2), 2020)

CostNet: An End-to-End Framework for Goal-Directed Reinforcement Learning. - Per-Arne Andersen; Morten Goodwin; Ole-Christoffer Granmo (SGAI Conf., 2020)

Towards safe reinforcement-learning in industrial grid-warehousing. - Per-Arne Andersen; Morten Goodwin; Ole-Christoffer Granmo (Inf. Sci., 2020)

ORACLE: End-to-End Model Based Reinforcement Learning. - Per-Arne Andersen; Morten Goodwin; Ole-Christoffer Granmo (SGAI Conf., 2021)

Increasing sample efficiency in deep reinforcement learning using generative environment modelling. - Per-Arne Andersen; Morten Goodwin; Ole-Christoffer Granmo (Expert Syst. J. Knowl. Eng., 2021)

Deep Q-Learning With Q-Matrix Transfer Learning for Novel Fire Evacuation Environment. - Jivitesh Sharma; Per-Arne Andersen; Ole-Christoffer Granmo; Morten Goodwin (IEEE Trans. Syst. Man Cybern. Syst., 2021)

CaiRL: A High-Performance Reinforcement Learning Environment Toolkit. - Per-Arne Andersen; Morten Goodwin; Ole-Christoffer Granmo (CoG, 2022)

The ODeLIndA Dataset for Field-of-View Obstruction Detection Using Transfer Learning for Real-Time Industrial Applications. - Abraham Anderson; Einar Julius Olafarson; Per-Arne Andersen; Nadia Saad Noori (SGAI Conf., 2022)

Synthetic data generated in Unreal Engine 4. - Sigurd Kvalsvik; Ingeborg Rasmussen; Daniel Hagen; Teodor Nilsen Aune; Per-Arne Andersen (IEEE DataPort, 2022)

DeNISE: Deep Networks for Improved Segmentation Edges. - Sander Riisøen Jyhne; Jørgen Åsbu Jacobsen; Morten Goodwin; Per-Arne Andersen (AIAI (1), 2023)

ReFrogID: Pattern Recognition for Pool Frog Identification Using Deep Learning and Feature Matching. - Vetle Nesland Evensen; Gabriel Bergman Henriksen; Sondre Melhus; Ole Steine Olsen; Kristina Haugen; Dag Dolmen; Arne Wiklund; Per-Arne Andersen; Morten Goodwin; Lars Mørch Korslund; Nadia Saad Noori (SGAI Conf., 2023)

A Contrastive Learning Scheme with Transformer Innate Patches. - Sander Riisøen Jyhne; Per-Arne Andersen; Morten Goodwin; Ivar Oveland (SGAI Conf., 2023)

Distinct Sequential Models for Inference Boosting. - Rune Alexander Laursen; Peshang Alo; Morten Goodwin; Per-Arne Andersen (SGAI Conf., 2023)

Contrastive Transformer: Contrastive Learning Scheme with Transformer innate Patches. - Sander Riisøen Jyhne; Per-Arne Andersen; Morten Goodwin (CoRR, 2023)

Loss and Reward Weighing for increased learning in Distributed Reinforcement Learning. - Martin Holen; Per-Arne Andersen; Kristian Muri Knausgård; Morten Goodwin (CoRR, 2023)

DeNISE: Deep Networks for Improved Segmentation Edges. - Sander Riisøen Jyhne; Per-Arne Andersen; Morten Goodwin (CoRR, 2023)

Learning Minimalistic Tsetlin Machine Clauses with Markov Boundary-Guided Pruning. - Ole-Christoffer Granmo; Per-Arne Andersen; Lei Jiao 001; Xuan Zhang 007; Christian D. Blakely; Tor Oddbjørn Tveit (CoRR, 2023)

Generalized Convergence Analysis of Tsetlin Machines: A Probabilistic Approach to Concept Learning. - Mohamed-Bachir Belaid; Jivitesh Sharma; Lei Jiao 001; Ole-Christoffer Granmo; Per-Arne Andersen; Anis Yazidi (CoRR, 2023)

Contracting Tsetlin Machine with Absorbing Automata. - Bimal Bhattarai; Ole-Christoffer Granmo; Lei Jiao 001; Per-Arne Andersen; Svein Anders Tunheim; Rishad A. Shafik; Alex Yakovlev (CoRR, 2023)

Towards Robust Road Quality Detection Using Different Detection Models. - Aayushi Vinod Thantharate; Morten Goodwin; Per-Arne Andersen; Aditya Gupta (AIAI (3), 2024)

PlanBERT: From Messy Zonal Plans to Informative Vector Embeddings. - Henrik Brådland; Morten Goodwin; Per-Arne Andersen; Alexander Salveson Nossum (SGAI Conf. (1), 2024)

NER Explainability Framework: Utilizing LIME to Enhance Clarity and Robustness in Named Entity Recognition. - Morten Grundetjern; Per-Arne Andersen; Morten Goodwin; Karl Audun Borgersen (SGAI Conf. (1), 2024)

TRAPL: Transformer-Based Patch Learning for Enhancing Semantic Representations Using Aggregated Features to Estimate Patch-Class Distribution. - Sander Riisøen Jyhne; Per-Arne Andersen; Ivar Oveland; Morten Goodwin (SGAI Conf. (1), 2024)

Exploring Efficient Job Shop Scheduling Using Deep Reinforcement Learning. - Reshma Maharjan; Per-Arne Andersen; Lei Jiao (SGAI Conf. (2), 2024)

MapAI: Precision in Building Segmentation. - Sander Riisøen Jyhne; Morten Goodwin; Per-Arne Andersen; Ivar Oveland; Alexander Salveson Nossum; Karianne Ormseth; Mathilde Ørstavik; Andrew C. Flatman (CoRR, 2024)

Exploring Effects of Hyperdimensional Vectors for Tsetlin Machines. - Vojtech Halenka; Ahmed K. Kadhim; Paul F. A. Clarke; Bimal Bhattarai; Rupsa Saha; Ole-Christoffer Granmo; Lei Jiao 001; Per-Arne Andersen (CoRR, 2024)

Towards safe and sustainable reinforcement learning for real-time strategy games. - Per-Arne Andersen; Morten Goodwin; Ole-Christoffer Granmo (Inf. Sci., 2024)

Generalized Convergence Analysis of Tsetlin Automaton Based Algorithms: A Probabilistic Approach to Concept Learning. - Mohamed-Bachir Belaid; Jivitesh Sharma; Lei Jiao 001; Ole-Christoffer Granmo; Per-Arne Andersen; Anis Yazidi (AAAI, 2025)

Implementing Hybrid Tsetlin Machine and Q-Learning for Solving the Job Shop Scheduling. - Reshma Maharjan; Per-Arne Andersen; Lei Jiao (EANN (1), 2025)

A New HOPE: Domain-agnostic Automatic Evaluation of Text Chunking. - Henrik Brådland; Morten Goodwin; Per-Arne Andersen; Alexander Salveson Nossum; Aditya Gupta (SIGIR, 2025)

The Tsetlin Machine Goes Deep: Logical Learning and Reasoning With Graphs. - Ole-Christoffer Granmo; Youmna Abdelwahab; Per-Arne Andersen; Paul F. A. Clarke; Kunal Ganesh Dumbre; Ylva Grønningsæter; Vojtech Halenka; Runar Helin; Lei Jiao 001; Ahmed Khalid; Rebekka Olsson Omslandseter; Rupsa Saha; et al. (CoRR, 2025)

A Comparative Study of Feature Selection in Tsetlin Machines. - Vojtech Halenka; Ole-Christoffer Granmo; Lei Jiao 001; Per-Arne Andersen (CoRR, 2025)