4 papers
Robust Exploration in Directed Controller Synthesis via Reinforcement Learning with Soft Mixture-of-Experts
Toshihide Ubukata, Zhiyao Wang, Enhong Mu +2
On-the-fly Directed Controller Synthesis (OTF-DCS) mitigates state-space explosion by incrementally exploring the system and relies critically on an exploration policy to guide sea…
Graph Contextual Reinforcement Learning for Efficient Directed Controller Synthesis
Toshihide Ubukata, Enhong Mu, Takuto Yamauchi +3
Controller synthesis is a formal method approach for automatically generating Labeled Transition System (LTS) controllers that satisfy specified properties. The efficiency of the s…
Synergizing Code Coverage and Gameplay Intent: Coverage-Aware Game Playtesting with LLM-Guided Reinforcement Learning
Enhong Mu, Minami Yoda, Yan Zhang +3
The widespread adoption of the "Games as a Service" model necessitates frequent content updates, placing immense pressure on quality assurance. In response, automated game testing…
Knowledge Graph-enhanced Large Language Model for Incremental Game PlayTesting
Enhong Mu, Jinyu Cai, Yijun Lu +3
The rapid iteration and frequent updates of modern video games pose significant challenges to the efficiency and specificity of testing. Although automated playtesting methods base…