4 papers
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…
Automatic Syntax Error Repair for Discrete Controller Synthesis using Large Language Model
Yusei Ishimizu, Takuto Yamauchi, Sinan Chen +3
Discrete Controller Synthesis (DCS) is a powerful formal method for automatically generating specifications of discrete event systems. However, its practical adoption is often hind…
Towards Context-aware Support for Color Vision Deficiency: An Approach Integrating LLM and AR
Shogo Morita, Yan Zhang, Takuto Yamauchi +3
People with color vision deficiency often face challenges in distinguishing colors such as red and green, which can complicate daily tasks and require the use of assistive tools or…
Exploring the Improvement of Evolutionary Computation via Large Language Models
Jinyu Cai, Jinglue Xu, Jialong Li +3
Evolutionary computation (EC), as a powerful optimization algorithm, has been applied across various domains. However, as the complexity of problems increases, the limitations of E…