Goal Oriented

Goal-oriented AI research focuses on developing artificial agents capable of autonomously pursuing and achieving specified objectives, addressing concerns about unintended consequences in advanced AI systems. Current research emphasizes improving the ability of large language models (LLMs) and reinforcement learning (RL) agents to engage in complex, multi-turn interactions, often incorporating external knowledge bases and employing techniques like knowledge distillation and planning algorithms (e.g., MCTS). This field is crucial for building safe and reliable AI systems across diverse applications, from customer service chatbots and space exploration to drug discovery and human-AI collaboration in decision-making.