Sequential Constant Size Compressors for Reinforcement Learning. - Linus Gisslén; Matthew D. Luciw; Vincent Graziano; Jürgen Schmidhuber (AGI, 2011)

Modular Value Iteration through Regional Decomposition. - Linus Gisslén; Mark B. Ring; Matthew D. Luciw; Jürgen Schmidhuber (AGI, 2012)

A Semantic Approach to Information Management and Decision Support: An Application to Humanitarian Demining Operations. - Linus Gisslén; Anders Törne (EISIC, 2015)

Dynamic and Context Aware Reporting of Observations from the Field for Situation Assessment in Crisis Situation: An Integrated System for Information-Gathering and Sense-Making. - Andreas Horndahl; Linus Gisslén (ISCRAM-med, 2015)

A Quantitative Approach to Risk and Cost Assessment in Supply Chain Management. - Linus Gisslén; Andreas Horndahl (EISIC, 2016)

Evaluating deep reinforcement learning for computer generated forces in ground combat simulation. - Babak Toghiani-Rizi; Farzad Kamrani; Linus J. Luotsinen; Linus Gisslén (SMC, 2017)

Imitation Learning with Concurrent Actions in 3D Games. - Jack Harmer; Linus Gisslén; Jorge del Val; Henrik Holst; Joakim Bergdahl; Tom Olsson; Kristoffer Sjöö; Magnus Nordin (CIG, 2018)

Imitation Learning with Concurrent Actions in 3D Games. - Jack Harmer; Linus Gisslén; Henrik Holst; Joakim Bergdahl; Tom Olsson; Kristoffer Sjöö; Magnus Nordin (CoRR, 2018)

Using Deep Convolutional Neural Networks to Detect Rendered Glitches in Video Games. - Carlos García Ling; Konrad Tollmar; Linus Gisslén (AIIDE, 2020)

Augmenting Automated Game Testing with Deep Reinforcement Learning. - Joakim Bergdahl; Camilo Gordillo; Konrad Tollmar; Linus Gisslén (CoG, 2020)

Adversarial Reinforcement Learning for Procedural Content Generation. - Linus Gisslén; Andy Eakins; Camilo Gordillo; Joakim Bergdahl; Konrad Tollmar (CoG, 2021)

Improving Playtesting Coverage via Curiosity Driven Reinforcement Learning Agents. - Camilo Gordillo; Joakim Bergdahl; Konrad Tollmar; Linus Gisslén (CoG, 2021)

Automatic Testing and Validation of Level of Detail Reductions Through Supervised Learning. - Matilda Tamm; Olivia Shamon; Hector Anadon Leon; Konrad Tollmar; Linus Gisslén (CoG, 2022)

CCPT: Automatic Gameplay Testing and Validation with Curiosity-Conditioned Proximal Trajectories. - Alessandro Sestini; Linus Gisslén; Joakim Bergdahl; Konrad Tollmar; Andrew D. Bagdanov (CoRR, 2022)

Generating Personas for Games with Multimodal Adversarial Imitation Learning. - William Ahlberg; Alessandro Sestini; Konrad Tollmar; Linus Gisslén (CoG, 2023)

Technical Challenges of Deploying Reinforcement Learning Agents for Game Testing in AAA Games. - Jonas Gillberg; Joakim Bergdahl; Alessandro Sestini; Andrew Eakins; Linus Gisslén (CoG, 2023)

Towards Informed Design and Validation Assistance in Computer Games Using Imitation Learning. - Alessandro Sestini; Joakim Bergdahl; Konrad Tollmar; Andrew D. Bagdanov; Linus Gisslén (CoG, 2023)

Improving Generalization in Game Agents with Data Augmentation in Imitation Learning. - Derek Yadgaroff; Alessandro Sestini; Konrad Tollmar; Linus Gisslén (CoRR, 2023)

Improving Generalization in Game Agents with Data Augmentation in Imitation Learning. - Derek Yadgaroff; Alessandro Sestini; Konrad Tollmar; Ayça Özçelikkale; Linus Gisslén (CEC, 2024)

Reinforcement Learning for High-Level Strategic Control in Tower Defense Games. - Joakim Bergdahl; Alessandro Sestini; Linus Gisslén (CoG, 2024)

Leveraging Large Language Models for Efficient Failure Analysis in Game Development. - Leonardo Marini; Linus Gisslén; Alessandro Sestini (CoG, 2024)

Automated Gameplay Testing and Validation With Curiosity-Conditioned Proximal Trajectories. - Alessandro Sestini; Linus Gisslén; Joakim Bergdahl; Konrad Tollmar; Andrew D. Bagdanov (IEEE Trans. Games, 2024)

Improving Conditional Level Generation Using Automated Validation in Match-3 Games. - Monica Villanueva Aylagas; Joakim Bergdahl; Jonas Gillberg; Alessandro Sestini; Theodor Tolstoy; Linus Gisslén (IEEE Trans. Games, 2024)

A Call for Deeper Collaboration Between Robotics and Game Development. - Iolanda Leite; William Ahlberg; André Pereira 001; Alessandro Sestini; Linus Gisslén; Konrad Tollmar (CoG, 2025)

Real-Time Diffusion Policies for Games: Enhancing Consistency Policies with Q-Ensembles. - Ruoqi Zhang; Ziwei Luo; Jens Sjölund; Per Mattsson; Linus Gisslén; Alessandro Sestini (CoG, 2025)

Towards Better Sample Efficiency in Multi-Agent Reinforcement Learning via Exploration. - Amir Baghi; Jens Sjölund; Joakim Bergdahl; Linus Gisslén; Alessandro Sestini (CoRR, 2025)

TROFI: Trajectory-Ranked Offline Inverse Reinforcement Learning. - Alessandro Sestini; Joakim Bergdahl; Konrad Tollmar; Andrew D. Bagdanov; Linus Gisslén (CoRR, 2025)

Self-correcting Reward Shaping via Language Models for Reinforcement Learning Agents in Games. - António Afonso; Iolanda Leite; Alessandro Sestini; Florian Fuchs; Konrad Tollmar; Linus Gisslén (CoRR, 2025)