5 citations · 6 across the 8 of their papers we have counts for
5 papers · 1 filter
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…
CCPT: Automatic Gameplay Testing and Validation with Curiosity-Conditioned Proximal Trajectories
Alessandro Sestini, Linus Gisslén, Joakim Bergdahl +2
This paper proposes a novel deep reinforcement learning algorithm to perform automatic analysis and detection of gameplay issues in complex 3D navigation environments. The Curiosit…
Augmenting Automated Game Testing with Deep Reinforcement Learning
Joakim Bergdahl, Camilo Gordillo, Konrad Tollmar +1
General game testing relies on the use of human play testers, play test scripting, and prior knowledge of areas of interest to produce relevant test data. Using deep reinforcement…
Improving Playtesting Coverage via Curiosity Driven Reinforcement Learning Agents
Camilo Gordillo, Joakim Bergdahl, Konrad Tollmar +1
As modern games continue growing both in size and complexity, it has become more challenging to ensure that all the relevant content is tested and that any potential issue is prope…
Adversarial Reinforcement Learning for Procedural Content Generation
Linus Gisslén, Andy Eakins, Camilo Gordillo +2
We present a new approach ARLPCG: Adversarial Reinforcement Learning for Procedural Content Generation, which procedurally generates and tests previously unseen environments with a…