Task Specification

Task specification research focuses on how to effectively define and represent tasks for intelligent systems, aiming to bridge the gap between human-understandable instructions and machine-executable commands. Current research emphasizes developing robust methods for representing tasks using various modalities, including natural language, visual data, and structured knowledge graphs, often leveraging large language models (LLMs) and reinforcement learning (RL) algorithms to achieve this. These advancements are crucial for improving the adaptability and generalizability of AI systems across diverse applications, from robotics and autonomous systems to natural language processing and personalized user interfaces. The ultimate goal is to enable more efficient and intuitive interaction between humans and intelligent systems, leading to more effective automation and problem-solving.