4 citations · 6 across the 8 of their papers we have counts for
8 papers
Improving Conditional Level Generation using Automated Validation in Match-3 Games
Monica Villanueva Aylagas, Joakim Bergdahl, Jonas Gillberg +3
Generative models for level generation have shown great potential in game production. However, they often provide limited control over the generation, and the validity of the gener…
A Benchmark Environment for Offline Reinforcement Learning in Racing Games
Girolamo Macaluso, Alessandro Sestini, Andrew D. Bagdanov
Offline Reinforcement Learning (ORL) is a promising approach to reduce the high sample complexity of traditional Reinforcement Learning (RL) by eliminating the need for continuous…
Reinforcement Learning for High-Level Strategic Control in Tower Defense Games
Joakim Bergdahl, Alessandro Sestini, Linus Gisslén
In strategy games, one of the most important aspects of game design is maintaining a sense of challenge for players. Many mobile titles feature quick gameplay loops that allow play…
Leveraging Large Language Models for Efficient Failure Analysis in Game Development
Leonardo Marini, Linus Gisslén, Alessandro Sestini
In games, and more generally in the field of software development, early detection of bugs is vital to maintain a high quality of the final product. Automated tests are a powerful…
Generating Personas for Games with Multimodal Adversarial Imitation Learning
William Ahlberg, Alessandro Sestini, Konrad Tollmar +1
Reinforcement learning has been widely successful in producing agents capable of playing games at a human level. However, this requires complex reward engineering, and the agent's…
Technical Challenges of Deploying Reinforcement Learning Agents for Game Testing in AAA Games
Jonas Gillberg, Joakim Bergdahl, Alessandro Sestini +2
Going from research to production, especially for large and complex software systems, is fundamentally a hard problem. In large-scale game production, one of the main reasons is th…