Task Planning

Task planning in artificial intelligence focuses on enabling agents, both virtual and robotic, to autonomously generate sequences of actions to achieve specified goals. Current research emphasizes improving the robustness and efficiency of planning methods, particularly using large language models (LLMs) and visual language models (VLMs), often integrated with symbolic planning techniques or reinforcement learning, to handle complex, long-horizon tasks and multi-agent scenarios. This field is crucial for advancing embodied AI, improving decision-making in various domains (e.g., disaster response, robotics, game design), and developing more reliable and adaptable autonomous systems.