Human intelligence thrives on the concept of cognitive synergy, where collaboration and information integration among different cognitive processes yield superior outcomes compared to individual cognitive processes in isolation. Although Large Language Models (LLMs) have demonstrated promising performance as general task-solving agents, they still struggle with tasks that require intensive domain knowledge and complex reasoning. In this work, we propose Solo Performance Prompting (SPP), which transforms a single LLM into a cognitive synergist by engaging in multi-turn self-collaboration with multiple personas. A cognitive synergist refers to an intelligent agent that collaborates with multiple minds, combining their individual strengths and knowledge, to enhance problem-solving and overall performance in complex tasks. By dynamically identifying and simulating different personas based on task inputs, SPP unleashes the potential of cognitive synergy in LLMs. We have discovered that assigning multiple, fine-grained personas in LLMs elicits better problem-solving abilities compared to using a single or fixed number of personas. We evaluate SPP on three challenging tasks: Trivia Creative Writing, Codenames Collaborative, and Logic Grid Puzzle, encompassing both knowledge-intensive and reasoning-intensive types. Unlike previous works, such as Chain-of-Thought, that solely enhance the reasoning abilities in LLMs, SPP effectively elicits internal knowledge acquisition abilities, reduces hallucination, and maintains strong reasoning capabilities. Code, data, and prompts can be found at: https://github.com/MikeWangWZHL/Solo-Performance-Prompting.git.

翻译：人类智能依赖于认知协同的概念，即不同认知过程之间的协作与信息整合相较于孤立认知过程能产生更优结果。尽管大语言模型（LLMs）作为通用任务求解智能体已展现出有前景的性能，但在需要密集领域知识和复杂推理的任务中仍存在困难。本文提出单机表演提示（SPP），通过让单个LLM以多角色进行多轮自我协作，将其转化为认知协同者。认知协同者指一种与多种心智协作的智能体，能够整合个体优势与知识，以提升复杂任务中的问题求解能力与整体表现。基于任务输入动态识别并模拟不同角色，SPP释放了LLMs中认知协同的潜力。我们发现，与使用单一或固定数量的角色相比，在LLMs中分配多个细粒度角色能激发更优的问题求解能力。我们在三个具有挑战性的任务上评估SPP：琐事创意写作、代号协作与逻辑网格谜题，涵盖知识密集型和推理密集型两种类型。与仅增强LLMs推理能力的先前工作（如思维链）不同，SPP有效激发了内部知识获取能力，减少了幻觉现象，并保持了强大的推理能力。代码、数据及提示可在以下链接获取：https://github.com/MikeWangWZHL/Solo-Performance-Prompting.git。