Task Graph Learning

Task Graph Learning refers to the construction and learning of directed acyclic graphs (DAGs) that represent procedural tasks, where nodes represent atomic actions or subtasks, and edges capture the dependencies or transitions between these actions. The goal of this task is to improve the efficiency and accuracy of task execution by optimizing the graph structure and the associations between nodes. It is widely applied in workflow management, automation systems, and complex task planning, among other fields.