Subtask Assignment

Subtask assignment focuses on efficiently decomposing complex tasks into smaller, manageable subtasks and assigning them to appropriate agents or modules, aiming to improve overall performance and scalability. Current research explores various approaches, including multi-agent reinforcement learning (MARL) frameworks with dynamic subtask allocation, graph neural networks for representing task dependencies, and methods leveraging large language models for both subtask identification and result integration. These advancements are significant for improving the efficiency and robustness of complex systems, with applications ranging from code generation and causality extraction to multi-agent robotics and data distillation.