Training RL agents to solve novel environments is a notoriously difficult task. Here we
present a new approach ARLPCG: Adversarial Reinforcement Learning for Procedural …

Large multimodal models (LMMs) have evolved from large language models (LLMs) to
integrate multiple input modalities such as visual inputs. This integration augments the …

Gameplay videos contain rich information about how players interact with the game and how
the game responds. Sharing gameplay videos on social media platforms, such as Reddit …

This paper presents a novel approach to automated playtesting for the prediction of human
player behavior and experience. We have previously demonstrated that Deep …

The HTML5 is used to display high quality graphics in web applications such as web games
(ie, games). However, automatically testing games is not possible with existing web testing …

Deep reinforcement learning (DRL) has attracted much attention in automated game testing.
Early attempts rely on game internal information for game space exploration, thus requiring …

Gameplay videos offer valuable insights into player interactions and game responses,
particularly data about game bugs. Despite the abundance of gameplay videos online …

Professional StarCraft game players are likely to focus on the management of the most
important group of units (called the main force) during gameplay. Although macro-level skills …

As video games evolve into expansive, detailed worlds, visual quality becomes essential,
yet increasingly challenging. Traditional testing methods, limited by resources, face …

Traditional methods of video game bug detection, such as manual testing, have been
effective, but they can also be time-consuming and costly. While Automated Bug Detection …