Discussion Mechanism

Research on discussion mechanisms explores how structured conversations between multiple agents, often large language models (LLMs), can enhance reasoning, creativity, and information processing. Current work focuses on developing effective discussion frameworks, including various multi-agent architectures and reinforcement learning techniques to optimize strategic communication and information exchange. These studies aim to understand the interplay between prompt engineering, discussion structure, and agent capabilities, ultimately seeking to improve LLM performance on complex tasks and potentially leading to more robust and creative AI systems.