Agent Planning

Agent planning focuses on enabling artificial intelligence agents to autonomously generate and execute plans to achieve complex goals, often interacting with humans and the environment. Current research emphasizes improving the efficiency and reliability of these plans, particularly using large language models (LLMs) as the core planning engine, often augmented by hierarchical planning structures, external tools, and human-in-the-loop interactions to address limitations like planning latency and hallucination. This field is crucial for advancing AI capabilities in diverse applications, from robotics and autonomous driving to cybersecurity and personalized task assistance, by creating more robust and reliable AI systems.